Preparación de la base
#2008-2018
lapop2004_2018$democracia7 <- lapop2004_2018$ing4
lapop2004_2018$democracia_ord <- lapop2004_2018$pn4
lapop2004_2018$reduc_desigualdad <- lapop2004_2018$ros4
lapop2004_2018 <- lapop2004_2018 %>%
mutate(voto_pasado = car::recode(vb2, "1=1; 2=0"),
voto_presente = car::recode(vb20, "1=0; c(2,3,4)=1"))
lapop2004_2018$country_f <- factor(lapop2004_2018$country,
labels = c("México", "Colombia", "Perú",
"Chile", "Uruguay", "Brasil", "Argentina"))
lapop2004_2018$sexo <- factor(lapop2004_2018$q1, labels = c("Varón", "Mujer"))
lapop2004_2018 <- lapop2004_2018 %>%
mutate(categoria_ocup = case_when((colocup4a <= 2 | ocup4a <= 2) & ocup1a == 3 ~ 1,
(colocup4a <= 2 | ocup4a <= 2) & ocup1a == 1 ~ 2,
(colocup4a <= 2 | ocup4a <= 2) & ocup1a == 2 ~ 3,
(colocup4a <= 2 | ocup4a <= 2) & ocup1a == 4 ~ 4,
(colocup4a == 3 |ocup4a == 3) | ocup1a == 5 ~ 5,
colocup4a >= 4 |ocup4a >= 4 ~ 6),
categoria_ocup_f = factor(categoria_ocup, labels = c("Patrón", "Asalariado público",
"Asalariado privado",
"Cuenta propia", "Desocupado",
"Inactivo")),
ing_decil = case_when(wave == 2008 | wave == 2010 ~ q10,
wave == 2012 ~ q10new_12,
wave == 2014 ~ q10new_14,
wave == 2016 ~ q10new_16,
wave == 2018 ~ q10new_18),
ideologia = car::recode(l1, "1=10; 2=9; 3=8; 4=7; 5=6; 6=5; 7=4; 8=3; 9=2; 10=1"))
#2018
lapop2004_2018$desempleados <- lapop2004_2018$redist3
lapop2004_2018$desempleados <- car::recode(lapop2004_2018$desempleados,
"7=1;6=2;5=3;4=4;3=5;2=6;1=7")
lapop2004_2018$ayuda_pobres <- lapop2004_2018$redist1
lapop2004_2018 <- lapop2004_2018 %>%
mutate(redist2_inv = ifelse(wave == 2018, car::recode(redist2, "1=7; 2=6; 3=5; 4=4; 5=3;
6=2; 7=1"), NA),
impuestos_ricos = ifelse(wave == 2018, case_when(country == 8 ~ redist2_inv,
TRUE ~ redist2a), NA),
corrup_func = car::recode(exc7, "1:2=0; 3:4=1"),
corrup_pol = car::recode(exc7new, "1:2=1; 3:5=0"),
golpe = car::recode(jc13, "2=1; 1=0"),
cierre_congreso = car::recode(jc15a, "2=1; 1=0"),
cierre_corte = car::recode(jc16a, "2=1; 1=0"),
simpatiza_partido = car::recode(vb10, "2=0"),
urbano = ifelse(wave == 2018, factor(ur, labels = c("Urbano", "Rural")), NA),
informal = ifelse(wave == 2018, car::recode(formal, "1=0; 2=1"), NA),
formal_f = ifelse(wave == 2018, factor(formal, labels = c("formal", "informal")), NA),
formal_estado = factor(ifelse(wave == 2018, case_when(formal == 1 ~ 1,
formal == 2 ~ 2,
categoria_ocup == 5 ~ 3,
categoria_ocup == 6 ~ 4,
TRUE ~ NA_real_), NA)),
formal_estado = factor(formal_estado, labels = c("Formal", "Informal", "Desocupado",
"Inactivo")),
formal_estado2 = factor(ifelse(wave == 2018, case_when(formal == 1 ~ 1,
formal == 2 ~ 2,
categoria_ocup >= 5 ~ 3,
TRUE ~ NA_real_), NA)),
formal_estado2 = factor(formal_estado2, labels = c("Formal", "Informal", "No ocupados")),
estatus_ocup = ifelse(wave == 2018, case_when(ocupoit <= 2 ~ 1,
ocupoit > 2 & ocupoit < 4 ~ 2,
ocupoit %in% c(5, 7, 8, 10) ~ 3,
ocupoit %in% c(6, 9) ~ 4,
categoria_ocup >= 5 ~ 5,
TRUE ~ NA_real_), NA),
estatus_ocup_f = factor(estatus_ocup, labels =
c("Directivos-Profesionales",
"Técnicos-administrativos-vendedores",
"Trabajadores manuales calificados",
"Trabajadores manuales no calificados",
"No ocupados")))
#Pegado bases
lapop2004_2018 <- lapop2004_2018 %>%
left_join(agregados, by = c("country_f", "wave"))
rm(paises_brecha, paises_desempleo, paises_empleopub, paises_informalidad)
Casos perdidos variables objetivo
Data Frame Summary
lapop2004_2018
Dimensions: 66771 x 2
Duplicates: 66707
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
democracia7
[numeric] |
| Mean (sd) : 5.2 (1.7) | | min ≤ med ≤ max: | | 1 ≤ 5 ≤ 7 | | IQR (CV) : 3 (0.3) |
|
| 1 | : | 2556 | ( | 4.0% | ) | | 2 | : | 2328 | ( | 3.6% | ) | | 3 | : | 5070 | ( | 7.9% | ) | | 4 | : | 10045 | ( | 15.7% | ) | | 5 | : | 12021 | ( | 18.8% | ) | | 6 | : | 11202 | ( | 17.5% | ) | | 7 | : | 20796 | ( | 32.5% | ) |
|
 |
2753
(4.1%) |
| 2 |
reduc_desigualdad
[numeric] |
| Mean (sd) : 5.7 (1.6) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 7 | | IQR (CV) : 2 (0.3) |
|
| 1 | : | 1931 | ( | 3.0% | ) | | 2 | : | 1659 | ( | 2.5% | ) | | 3 | : | 2978 | ( | 4.6% | ) | | 4 | : | 6419 | ( | 9.8% | ) | | 5 | : | 9795 | ( | 15.0% | ) | | 6 | : | 12511 | ( | 19.2% | ) | | 7 | : | 29897 | ( | 45.9% | ) |
|
 |
1581
(2.4%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
Democracia 7 categorías x onda
|
|
2008
|
2010
|
2012
|
2014
|
2016
|
2018
|
NA
|
|
1
|
3.08
|
3.31
|
2.74
|
3.27
|
5.74
|
4.61
|
NaN
|
|
2
|
3.06
|
3.26
|
2.94
|
2.96
|
4.92
|
3.61
|
NaN
|
|
3
|
6.20
|
6.58
|
7.31
|
7.31
|
9.52
|
8.47
|
NaN
|
|
4
|
12.52
|
13.05
|
13.31
|
13.52
|
18.58
|
18.93
|
NaN
|
|
5
|
15.59
|
16.29
|
16.97
|
17.98
|
19.62
|
21.45
|
NaN
|
|
6
|
19.58
|
17.81
|
18.66
|
15.75
|
14.37
|
14.75
|
NaN
|
|
7
|
34.71
|
34.26
|
34.30
|
34.90
|
24.27
|
25.13
|
NaN
|
|
NA
|
5.25
|
5.43
|
3.77
|
4.28
|
2.98
|
3.05
|
NaN
|
Democracia 7 categorías x educación
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
5.14
|
6.81
|
4.44
|
4.20
|
3.72
|
4.81
|
3.92
|
4.27
|
4.39
|
4.47
|
3.96
|
4.03
|
3.20
|
3.11
|
2.85
|
2.67
|
2.62
|
2.26
|
2.94
|
10.34
|
|
2
|
4.64
|
5.40
|
5.00
|
4.35
|
4.00
|
4.50
|
3.07
|
3.91
|
3.73
|
3.47
|
2.98
|
4.23
|
2.70
|
3.38
|
3.02
|
2.18
|
2.45
|
2.17
|
2.88
|
7.13
|
|
3
|
7.30
|
8.10
|
8.39
|
8.07
|
8.40
|
8.28
|
7.44
|
7.59
|
7.72
|
8.23
|
7.27
|
9.47
|
6.79
|
7.15
|
6.94
|
4.64
|
6.78
|
4.11
|
5.28
|
10.57
|
|
4
|
12.69
|
11.97
|
12.82
|
13.38
|
12.53
|
14.77
|
14.32
|
13.00
|
15.79
|
17.25
|
14.10
|
18.23
|
15.30
|
14.70
|
15.93
|
11.87
|
13.12
|
10.99
|
13.18
|
17.93
|
|
5
|
15.26
|
15.73
|
15.32
|
17.15
|
18.03
|
17.86
|
16.36
|
17.01
|
19.46
|
20.10
|
16.63
|
20.35
|
18.45
|
19.01
|
18.65
|
15.41
|
15.95
|
14.41
|
15.38
|
19.08
|
|
6
|
12.11
|
13.38
|
16.85
|
16.67
|
18.39
|
17.24
|
17.05
|
16.10
|
16.92
|
15.27
|
15.43
|
16.74
|
17.38
|
17.06
|
18.82
|
16.72
|
18.93
|
18.94
|
14.25
|
11.49
|
|
7
|
26.78
|
25.00
|
25.24
|
26.71
|
26.84
|
24.53
|
31.73
|
33.08
|
27.34
|
27.60
|
36.15
|
24.63
|
33.32
|
33.72
|
32.69
|
45.52
|
39.19
|
46.33
|
45.22
|
14.94
|
|
NA
|
16.09
|
13.62
|
11.94
|
9.46
|
8.08
|
8.00
|
6.12
|
5.04
|
4.65
|
3.62
|
3.47
|
2.32
|
2.86
|
1.87
|
1.10
|
0.99
|
0.94
|
0.79
|
0.87
|
8.51
|
Democracia 7 categorías x ocupación
|
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
NA
|
|
1
|
4.40
|
2.71
|
3.26
|
4.22
|
4.95
|
3.82
|
5.33
|
|
2
|
3.60
|
2.81
|
2.85
|
3.92
|
4.09
|
3.59
|
3.13
|
|
3
|
7.45
|
6.35
|
6.75
|
8.15
|
9.10
|
7.61
|
9.72
|
|
4
|
13.37
|
12.84
|
14.84
|
15.84
|
18.21
|
14.52
|
15.52
|
|
5
|
15.37
|
16.41
|
17.58
|
18.45
|
20.37
|
17.89
|
18.81
|
|
6
|
16.41
|
17.15
|
17.48
|
16.57
|
15.12
|
16.92
|
12.07
|
|
7
|
37.47
|
40.01
|
34.63
|
28.87
|
24.39
|
30.11
|
26.02
|
|
NA
|
1.92
|
1.73
|
2.62
|
3.99
|
3.77
|
5.54
|
9.40
|
Democracia 7 categorías x ingresos (decil)
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
8.25
|
5.75
|
4.96
|
4.06
|
3.99
|
3.76
|
3.46
|
3.43
|
3.20
|
2.73
|
2.87
|
3.48
|
3.36
|
4.01
|
3.42
|
3.35
|
3.43
|
3.24
|
|
2
|
6.53
|
4.29
|
3.73
|
4.13
|
3.99
|
3.39
|
3.60
|
3.43
|
3.31
|
2.95
|
3.09
|
2.73
|
2.83
|
2.82
|
2.99
|
3.01
|
3.02
|
3.19
|
|
3
|
9.11
|
9.15
|
8.66
|
8.57
|
7.91
|
7.91
|
8.37
|
7.87
|
6.65
|
7.53
|
6.66
|
8.52
|
7.52
|
7.12
|
5.75
|
6.30
|
6.16
|
6.17
|
|
4
|
17.86
|
16.26
|
15.25
|
15.13
|
15.11
|
16.84
|
15.13
|
15.57
|
15.12
|
15.47
|
14.22
|
15.87
|
16.99
|
16.53
|
15.01
|
13.29
|
10.71
|
13.41
|
|
5
|
16.38
|
17.51
|
19.42
|
18.46
|
17.85
|
18.55
|
18.68
|
18.07
|
18.46
|
17.92
|
18.81
|
19.73
|
19.78
|
17.53
|
19.48
|
16.35
|
14.07
|
16.49
|
|
6
|
12.07
|
14.38
|
15.74
|
16.29
|
17.79
|
18.36
|
18.64
|
17.71
|
17.16
|
17.45
|
17.88
|
15.35
|
16.26
|
16.77
|
16.20
|
17.89
|
16.87
|
16.32
|
|
7
|
22.29
|
24.58
|
26.15
|
27.83
|
29.51
|
28.22
|
29.24
|
31.18
|
33.37
|
33.40
|
34.33
|
31.97
|
31.19
|
33.35
|
35.96
|
38.39
|
44.97
|
33.99
|
|
NA
|
7.51
|
8.07
|
6.08
|
5.52
|
3.85
|
2.98
|
2.88
|
2.74
|
2.74
|
2.54
|
2.14
|
2.35
|
2.06
|
1.86
|
1.19
|
1.42
|
0.77
|
7.19
|
Reducción de la desigualdad x onda
|
|
2008
|
2010
|
2012
|
2014
|
2016
|
2018
|
NA
|
|
1
|
2.01
|
1.64
|
1.58
|
2.98
|
4.39
|
4.63
|
NaN
|
|
2
|
1.74
|
1.76
|
1.41
|
2.92
|
3.64
|
3.35
|
NaN
|
|
3
|
3.16
|
3.19
|
2.98
|
4.72
|
5.74
|
6.88
|
NaN
|
|
4
|
7.01
|
7.16
|
8.54
|
9.88
|
11.54
|
13.46
|
NaN
|
|
5
|
12.40
|
12.96
|
14.83
|
14.89
|
15.68
|
17.23
|
NaN
|
|
6
|
20.15
|
20.02
|
20.50
|
17.25
|
17.71
|
16.85
|
NaN
|
|
7
|
49.80
|
50.26
|
47.97
|
44.63
|
39.78
|
36.50
|
NaN
|
|
NA
|
3.74
|
3.01
|
2.18
|
2.73
|
1.53
|
1.10
|
NaN
|
Reducción desigualdad x educación
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
5.31
|
5.16
|
4.03
|
3.73
|
3.27
|
3.16
|
3.12
|
3.36
|
2.84
|
3.10
|
2.58
|
2.53
|
2.24
|
2.27
|
2.46
|
2.38
|
2.42
|
2.36
|
4.15
|
8.28
|
|
2
|
2.57
|
3.52
|
3.71
|
3.20
|
2.82
|
2.89
|
2.62
|
2.04
|
2.31
|
2.56
|
2.69
|
2.46
|
1.83
|
2.27
|
2.26
|
2.47
|
2.51
|
1.62
|
2.88
|
7.59
|
|
3
|
4.56
|
5.05
|
5.08
|
4.49
|
4.50
|
4.43
|
4.17
|
4.02
|
4.28
|
4.34
|
3.63
|
5.02
|
3.92
|
4.58
|
4.58
|
4.35
|
5.19
|
4.11
|
5.35
|
5.52
|
|
4
|
7.30
|
6.34
|
7.34
|
9.99
|
8.58
|
8.86
|
8.41
|
9.16
|
7.72
|
9.74
|
8.54
|
10.59
|
9.89
|
9.37
|
11.52
|
9.65
|
10.29
|
10.25
|
13.44
|
14.94
|
|
5
|
13.10
|
12.68
|
12.98
|
12.04
|
11.90
|
13.47
|
13.40
|
13.87
|
13.90
|
14.78
|
13.75
|
16.51
|
16.04
|
15.37
|
16.30
|
14.13
|
15.07
|
13.58
|
14.38
|
14.25
|
|
6
|
14.59
|
16.78
|
18.79
|
18.06
|
17.21
|
18.83
|
17.21
|
17.38
|
18.52
|
17.48
|
17.85
|
20.19
|
19.00
|
20.97
|
20.88
|
19.80
|
20.85
|
18.66
|
17.06
|
12.87
|
|
7
|
42.04
|
42.14
|
41.53
|
42.90
|
46.50
|
45.04
|
48.18
|
47.06
|
48.17
|
46.16
|
48.63
|
41.33
|
45.36
|
44.47
|
41.45
|
46.01
|
42.94
|
48.50
|
41.54
|
30.34
|
|
NA
|
10.53
|
8.33
|
6.53
|
5.59
|
5.22
|
3.33
|
2.89
|
3.10
|
2.26
|
1.86
|
2.33
|
1.38
|
1.72
|
0.71
|
0.56
|
1.19
|
0.74
|
0.92
|
1.20
|
6.21
|
Reducción desigualdad x ocupación
|
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
NA
|
|
1
|
4.16
|
2.36
|
2.38
|
3.16
|
3.05
|
2.96
|
5.17
|
|
2
|
2.72
|
1.91
|
2.16
|
2.89
|
2.39
|
2.54
|
2.35
|
|
3
|
5.44
|
3.74
|
4.13
|
4.58
|
4.60
|
4.60
|
5.80
|
|
4
|
10.89
|
8.69
|
9.30
|
10.16
|
9.04
|
9.66
|
10.97
|
|
5
|
14.97
|
14.11
|
15.10
|
14.67
|
14.27
|
14.63
|
13.95
|
|
6
|
20.26
|
20.11
|
18.92
|
18.77
|
18.04
|
18.51
|
15.67
|
|
7
|
40.91
|
47.69
|
46.62
|
43.66
|
46.94
|
43.72
|
40.44
|
|
NA
|
0.64
|
1.40
|
1.40
|
2.12
|
1.67
|
3.38
|
5.64
|
Reducción desigualdad x ingresos (decil)
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
4.56
|
3.98
|
2.43
|
3.09
|
2.54
|
2.63
|
2.45
|
2.19
|
2.33
|
2.01
|
3.22
|
2.45
|
2.47
|
2.91
|
2.66
|
3.29
|
4.56
|
3.34
|
|
2
|
4.80
|
3.31
|
2.64
|
2.15
|
2.19
|
2.59
|
2.26
|
2.36
|
2.36
|
2.64
|
2.26
|
2.97
|
2.35
|
2.48
|
2.52
|
2.44
|
2.92
|
2.10
|
|
3
|
5.91
|
4.16
|
4.19
|
3.89
|
4.07
|
4.19
|
4.12
|
4.25
|
4.64
|
4.49
|
5.39
|
3.86
|
4.98
|
4.25
|
4.89
|
4.32
|
5.36
|
4.97
|
|
4
|
11.45
|
8.88
|
8.01
|
8.31
|
8.74
|
9.19
|
9.41
|
8.99
|
10.42
|
10.45
|
9.60
|
10.69
|
11.17
|
9.89
|
10.40
|
11.98
|
11.59
|
10.26
|
|
5
|
12.44
|
12.17
|
13.40
|
14.35
|
14.06
|
14.79
|
15.92
|
14.40
|
14.60
|
15.13
|
14.50
|
15.11
|
16.18
|
17.20
|
17.10
|
16.41
|
15.60
|
14.64
|
|
6
|
14.78
|
16.10
|
18.85
|
18.91
|
19.17
|
20.75
|
19.64
|
20.48
|
19.61
|
20.09
|
20.62
|
18.27
|
19.78
|
19.35
|
18.76
|
17.49
|
17.42
|
16.54
|
|
7
|
41.75
|
47.17
|
47.05
|
46.73
|
47.19
|
44.10
|
44.54
|
45.32
|
44.34
|
44.22
|
43.29
|
45.53
|
42.03
|
42.76
|
42.61
|
43.50
|
41.95
|
43.30
|
|
NA
|
4.31
|
4.23
|
3.42
|
2.57
|
2.04
|
1.76
|
1.64
|
2.00
|
1.70
|
0.97
|
1.12
|
1.13
|
1.05
|
1.15
|
1.05
|
0.57
|
0.62
|
4.85
|
Data Frame Summary
lapop2018
Dimensions: 11009 x 3
Duplicates: 10569
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
desempleados
[numeric] |
| Mean (sd) : 3.4 (2) | | min ≤ med ≤ max: | | 1 ≤ 3 ≤ 7 | | IQR (CV) : 3 (0.6) |
|
| 1 | : | 2549 | ( | 23.3% | ) | | 2 | : | 1612 | ( | 14.7% | ) | | 3 | : | 1897 | ( | 17.3% | ) | | 4 | : | 1579 | ( | 14.4% | ) | | 5 | : | 1167 | ( | 10.7% | ) | | 6 | : | 908 | ( | 8.3% | ) | | 7 | : | 1222 | ( | 11.2% | ) |
|
 |
75
(0.7%) |
| 2 |
impuestos_ricos
[numeric] |
| Mean (sd) : 4.3 (1.9) | | min ≤ med ≤ max: | | 1 ≤ 4 ≤ 7 | | IQR (CV) : 3 (0.4) |
|
| 1 | : | 1268 | ( | 11.8% | ) | | 2 | : | 861 | ( | 8.0% | ) | | 3 | : | 1306 | ( | 12.2% | ) | | 4 | : | 2252 | ( | 21.0% | ) | | 5 | : | 1962 | ( | 18.3% | ) | | 6 | : | 1253 | ( | 11.7% | ) | | 7 | : | 1838 | ( | 17.1% | ) |
|
 |
269
(2.4%) |
| 3 |
ayuda_pobres
[numeric] |
| Mean (sd) : 5.5 (1.8) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 7 | | IQR (CV) : 3 (0.3) |
|
| 1 | : | 505 | ( | 4.6% | ) | | 2 | : | 379 | ( | 3.5% | ) | | 3 | : | 640 | ( | 5.8% | ) | | 4 | : | 1294 | ( | 11.8% | ) | | 5 | : | 1501 | ( | 13.7% | ) | | 6 | : | 1734 | ( | 15.8% | ) | | 7 | : | 4893 | ( | 44.7% | ) |
|
 |
63
(0.6%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
Desempleados x educación
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
26.92
|
29.41
|
21.48
|
26.55
|
28.33
|
27.59
|
25.54
|
26.10
|
28.64
|
28.10
|
23.86
|
21.17
|
24.90
|
18.55
|
18.33
|
17.15
|
15.38
|
18.82
|
17.16
|
19.78
|
|
2
|
15.38
|
13.73
|
17.45
|
18.18
|
14.68
|
17.00
|
17.63
|
14.09
|
15.08
|
16.94
|
14.39
|
13.96
|
13.03
|
12.53
|
15.68
|
12.47
|
14.17
|
12.47
|
12.19
|
19.78
|
|
3
|
13.85
|
12.75
|
18.12
|
14.91
|
13.99
|
18.47
|
19.42
|
15.24
|
15.93
|
19.42
|
14.96
|
18.42
|
18.26
|
18.55
|
20.77
|
14.70
|
16.60
|
12.02
|
14.00
|
14.29
|
|
4
|
10.77
|
9.80
|
10.07
|
12.36
|
11.95
|
9.61
|
11.39
|
12.24
|
12.37
|
11.98
|
16.10
|
14.95
|
16.06
|
15.66
|
17.72
|
16.93
|
15.38
|
16.55
|
18.06
|
17.58
|
|
5
|
8.46
|
8.82
|
10.74
|
10.55
|
10.92
|
10.59
|
7.55
|
9.70
|
9.15
|
7.85
|
8.90
|
11.21
|
10.58
|
11.57
|
11.81
|
15.14
|
14.17
|
14.29
|
11.29
|
8.79
|
|
6
|
6.15
|
6.86
|
8.05
|
6.55
|
6.83
|
5.91
|
6.83
|
8.55
|
6.10
|
7.23
|
8.90
|
7.73
|
7.74
|
8.19
|
7.94
|
8.69
|
11.74
|
14.51
|
13.54
|
9.89
|
|
7
|
15.38
|
16.67
|
10.74
|
8.73
|
11.95
|
9.85
|
11.03
|
13.63
|
12.37
|
7.54
|
11.93
|
12.04
|
8.90
|
14.70
|
7.54
|
14.92
|
11.94
|
11.11
|
13.32
|
8.79
|
|
NA
|
3.08
|
1.96
|
3.36
|
2.18
|
1.37
|
0.99
|
0.60
|
0.46
|
0.34
|
0.93
|
0.95
|
0.52
|
0.52
|
0.24
|
0.20
|
0.00
|
0.61
|
0.23
|
0.45
|
1.10
|
Desempleados x ocupación
|
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
NA
|
|
1
|
28.08
|
22.09
|
23.30
|
24.52
|
22.16
|
22.42
|
25.93
|
|
2
|
16.54
|
12.29
|
14.57
|
14.83
|
13.23
|
15.15
|
19.26
|
|
3
|
16.15
|
15.95
|
17.88
|
18.43
|
14.85
|
17.32
|
14.81
|
|
4
|
15.38
|
15.95
|
15.48
|
14.06
|
13.15
|
13.96
|
13.33
|
|
5
|
10.77
|
11.24
|
10.83
|
9.34
|
9.33
|
11.46
|
9.63
|
|
6
|
5.77
|
11.24
|
8.01
|
7.72
|
8.12
|
8.29
|
8.89
|
|
7
|
7.31
|
11.11
|
9.78
|
10.37
|
18.34
|
10.41
|
6.67
|
|
NA
|
0.00
|
0.13
|
0.14
|
0.73
|
0.81
|
1.00
|
1.48
|
Desempleados x ingresos (decil)
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
27.35
|
27.35
|
25.75
|
25.76
|
26.87
|
20.29
|
23.71
|
19.06
|
21.72
|
24.47
|
24.80
|
21.12
|
22.51
|
19.59
|
20.62
|
22.84
|
20.24
|
22.76
|
|
2
|
12.56
|
15.15
|
15.45
|
13.96
|
13.67
|
14.17
|
17.26
|
13.81
|
13.10
|
16.18
|
15.76
|
14.15
|
15.01
|
13.86
|
16.32
|
13.53
|
13.38
|
14.53
|
|
3
|
13.45
|
16.18
|
17.34
|
15.40
|
14.94
|
19.48
|
17.58
|
19.41
|
18.74
|
17.53
|
16.38
|
19.57
|
19.70
|
19.96
|
16.49
|
15.96
|
15.09
|
16.45
|
|
4
|
8.52
|
11.91
|
12.06
|
12.81
|
11.13
|
15.94
|
13.23
|
18.36
|
16.75
|
16.96
|
17.16
|
15.31
|
14.26
|
14.97
|
13.23
|
15.08
|
15.95
|
13.70
|
|
5
|
10.31
|
8.82
|
9.67
|
10.50
|
10.17
|
11.43
|
10.32
|
10.14
|
10.28
|
8.48
|
9.83
|
11.43
|
14.07
|
13.68
|
10.48
|
9.09
|
13.21
|
10.05
|
|
6
|
9.42
|
7.65
|
7.54
|
8.06
|
6.36
|
8.53
|
6.94
|
9.27
|
7.46
|
7.32
|
6.55
|
8.91
|
6.57
|
8.32
|
11.17
|
10.64
|
10.46
|
8.72
|
|
7
|
15.25
|
11.91
|
11.81
|
12.95
|
15.90
|
8.70
|
10.48
|
9.79
|
11.61
|
9.06
|
9.20
|
8.72
|
7.69
|
9.43
|
11.34
|
11.97
|
11.49
|
12.29
|
|
NA
|
3.14
|
1.03
|
0.38
|
0.58
|
0.95
|
1.45
|
0.48
|
0.17
|
0.33
|
0.00
|
0.31
|
0.78
|
0.19
|
0.18
|
0.34
|
0.89
|
0.17
|
1.50
|
Ayuda pobres x educación
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
11.54
|
5.88
|
5.37
|
3.64
|
3.75
|
3.20
|
5.04
|
3.93
|
4.24
|
4.55
|
7.58
|
2.65
|
4.26
|
3.13
|
3.87
|
6.01
|
5.47
|
7.71
|
7.67
|
3.30
|
|
2
|
2.31
|
5.88
|
1.34
|
0.73
|
1.71
|
1.48
|
3.84
|
2.08
|
2.88
|
2.79
|
3.98
|
2.54
|
3.68
|
3.13
|
4.07
|
6.90
|
6.28
|
5.44
|
4.51
|
4.40
|
|
3
|
3.08
|
7.84
|
3.36
|
5.09
|
2.73
|
2.22
|
3.60
|
5.31
|
4.07
|
4.55
|
5.68
|
4.26
|
6.52
|
8.67
|
8.15
|
9.80
|
7.49
|
9.98
|
12.19
|
3.30
|
|
4
|
9.23
|
6.86
|
8.72
|
8.00
|
4.10
|
3.69
|
7.91
|
6.24
|
6.95
|
9.50
|
13.64
|
8.72
|
16.00
|
16.39
|
16.50
|
18.04
|
16.80
|
20.18
|
20.09
|
8.79
|
|
5
|
9.23
|
3.92
|
8.05
|
9.82
|
9.90
|
10.84
|
11.87
|
11.55
|
11.02
|
11.16
|
10.23
|
14.17
|
14.52
|
15.90
|
14.66
|
18.04
|
19.64
|
20.18
|
17.83
|
16.48
|
|
6
|
13.08
|
9.80
|
15.44
|
13.82
|
15.70
|
14.78
|
17.51
|
15.47
|
14.41
|
16.63
|
13.26
|
16.81
|
15.29
|
16.63
|
18.74
|
13.81
|
18.02
|
12.47
|
15.58
|
15.38
|
|
7
|
50.00
|
58.82
|
57.05
|
57.82
|
61.43
|
63.55
|
48.80
|
55.20
|
56.10
|
50.41
|
45.27
|
50.34
|
39.29
|
35.90
|
33.81
|
26.50
|
25.71
|
23.13
|
21.90
|
47.25
|
|
NA
|
1.54
|
0.98
|
0.67
|
1.09
|
0.68
|
0.25
|
1.44
|
0.23
|
0.34
|
0.41
|
0.38
|
0.52
|
0.45
|
0.24
|
0.20
|
0.89
|
0.61
|
0.91
|
0.23
|
1.10
|
Ayuda pobres x ocupación
|
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
NA
|
|
1
|
4.62
|
5.36
|
5.80
|
4.59
|
3.81
|
4.05
|
5.19
|
|
2
|
3.85
|
5.49
|
3.98
|
3.34
|
3.08
|
2.98
|
2.22
|
|
3
|
7.69
|
7.32
|
7.09
|
5.49
|
4.22
|
5.48
|
4.44
|
|
4
|
11.92
|
14.77
|
14.09
|
10.93
|
10.15
|
11.01
|
10.37
|
|
5
|
16.92
|
17.12
|
14.09
|
13.80
|
11.85
|
12.96
|
14.81
|
|
6
|
15.38
|
13.99
|
14.81
|
15.65
|
14.69
|
17.03
|
12.59
|
|
7
|
39.23
|
35.42
|
39.98
|
45.48
|
51.87
|
45.76
|
48.15
|
|
NA
|
0.38
|
0.52
|
0.14
|
0.73
|
0.32
|
0.74
|
2.22
|
Ayuda pobres x ingresos (decil)
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
7.17
|
2.94
|
3.52
|
3.17
|
4.77
|
4.35
|
3.55
|
4.55
|
4.31
|
4.24
|
5.15
|
4.84
|
3.94
|
4.81
|
6.70
|
5.54
|
6.00
|
5.15
|
|
2
|
2.24
|
2.35
|
2.51
|
2.30
|
1.91
|
2.74
|
2.42
|
3.50
|
3.98
|
3.66
|
3.28
|
3.49
|
3.19
|
4.81
|
3.61
|
5.99
|
6.69
|
3.82
|
|
3
|
2.69
|
3.68
|
2.89
|
6.33
|
4.29
|
4.51
|
4.52
|
5.77
|
5.14
|
6.17
|
6.55
|
5.43
|
7.69
|
7.58
|
7.90
|
8.65
|
9.61
|
5.81
|
|
4
|
6.73
|
6.18
|
8.17
|
8.92
|
8.11
|
10.47
|
12.26
|
11.71
|
11.28
|
14.07
|
11.86
|
13.37
|
14.26
|
14.05
|
14.26
|
19.96
|
17.50
|
11.46
|
|
5
|
8.52
|
7.94
|
10.93
|
10.07
|
13.83
|
14.17
|
14.84
|
12.59
|
10.78
|
14.07
|
15.44
|
16.28
|
16.70
|
16.64
|
16.15
|
14.19
|
19.55
|
13.29
|
|
6
|
12.11
|
15.59
|
16.71
|
17.70
|
15.26
|
16.43
|
17.58
|
14.86
|
15.75
|
17.53
|
14.98
|
16.09
|
17.45
|
15.90
|
15.98
|
17.29
|
11.15
|
14.37
|
|
7
|
60.09
|
60.44
|
54.90
|
50.94
|
51.35
|
46.22
|
44.19
|
46.50
|
47.76
|
40.27
|
42.75
|
40.50
|
36.40
|
35.86
|
35.40
|
27.94
|
28.64
|
44.85
|
|
NA
|
0.45
|
0.88
|
0.38
|
0.58
|
0.48
|
1.13
|
0.65
|
0.52
|
1.00
|
0.00
|
0.00
|
0.00
|
0.38
|
0.37
|
0.00
|
0.44
|
0.86
|
1.25
|
Impuestos ricos x educación
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
16.15
|
17.65
|
12.75
|
13.09
|
13.99
|
14.78
|
10.55
|
13.16
|
12.20
|
11.57
|
12.69
|
13.03
|
9.03
|
9.16
|
8.35
|
10.47
|
9.92
|
11.11
|
11.74
|
10.99
|
|
2
|
11.54
|
5.88
|
8.05
|
8.36
|
8.53
|
9.36
|
7.31
|
6.00
|
7.63
|
6.10
|
8.71
|
10.07
|
5.55
|
5.30
|
7.94
|
6.90
|
9.72
|
7.48
|
9.93
|
8.79
|
|
3
|
5.38
|
11.76
|
14.09
|
13.45
|
10.58
|
12.56
|
10.79
|
9.93
|
9.15
|
9.92
|
13.45
|
14.32
|
10.00
|
12.05
|
13.65
|
11.80
|
10.73
|
12.24
|
16.03
|
15.38
|
|
4
|
15.38
|
11.76
|
17.45
|
18.91
|
14.68
|
15.52
|
15.35
|
18.01
|
19.15
|
20.87
|
19.70
|
19.93
|
23.68
|
23.37
|
24.64
|
22.72
|
25.71
|
19.95
|
24.83
|
16.48
|
|
5
|
16.92
|
9.80
|
13.42
|
11.27
|
15.02
|
14.53
|
20.02
|
17.32
|
15.93
|
18.90
|
16.48
|
16.71
|
20.71
|
23.13
|
17.31
|
18.04
|
17.61
|
21.54
|
14.90
|
18.68
|
|
6
|
9.23
|
9.80
|
10.74
|
12.00
|
10.58
|
11.82
|
12.83
|
12.93
|
13.90
|
12.09
|
8.71
|
10.33
|
12.71
|
11.08
|
13.85
|
9.80
|
9.11
|
10.88
|
9.48
|
6.59
|
|
7
|
20.00
|
24.51
|
18.12
|
18.55
|
20.14
|
18.23
|
19.30
|
21.02
|
20.17
|
18.18
|
17.42
|
14.06
|
15.81
|
13.73
|
13.44
|
18.93
|
15.18
|
15.19
|
11.96
|
19.78
|
|
NA
|
5.38
|
8.82
|
5.37
|
4.36
|
6.48
|
3.20
|
3.84
|
1.62
|
1.86
|
2.38
|
2.84
|
1.56
|
2.52
|
2.17
|
0.81
|
1.34
|
2.02
|
1.59
|
1.13
|
3.30
|
Impuestos ricos x ocupación
|
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
NA
|
|
1
|
9.23
|
11.24
|
10.64
|
12.39
|
13.31
|
11.05
|
14.07
|
|
2
|
8.85
|
6.80
|
6.71
|
8.02
|
8.04
|
8.34
|
7.41
|
|
3
|
13.46
|
11.50
|
11.98
|
11.40
|
11.69
|
12.17
|
8.89
|
|
4
|
23.46
|
21.96
|
21.52
|
21.30
|
19.89
|
19.34
|
14.81
|
|
5
|
20.00
|
18.30
|
19.32
|
16.89
|
17.37
|
17.53
|
17.04
|
|
6
|
7.31
|
11.63
|
11.89
|
10.89
|
9.82
|
12.01
|
13.33
|
|
7
|
17.31
|
16.99
|
16.78
|
17.36
|
17.53
|
15.84
|
20.00
|
|
NA
|
0.38
|
1.57
|
1.15
|
1.76
|
2.35
|
3.72
|
4.44
|
Impuestos ricos x ingresos (decil)
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
17.49
|
15.44
|
11.56
|
11.08
|
13.67
|
9.98
|
10.00
|
9.27
|
8.96
|
11.75
|
11.70
|
8.91
|
7.88
|
11.09
|
13.92
|
12.42
|
13.21
|
11.63
|
|
2
|
13.45
|
8.24
|
7.29
|
9.35
|
9.06
|
7.41
|
6.45
|
5.94
|
6.80
|
5.59
|
8.11
|
9.11
|
6.57
|
7.02
|
9.79
|
8.87
|
9.61
|
6.64
|
|
3
|
8.52
|
11.62
|
12.81
|
11.22
|
11.61
|
11.59
|
11.13
|
12.06
|
10.28
|
11.95
|
11.08
|
10.47
|
12.76
|
13.49
|
11.51
|
14.19
|
14.41
|
11.63
|
|
4
|
15.70
|
15.00
|
18.47
|
20.00
|
17.17
|
18.36
|
21.94
|
24.30
|
21.56
|
22.35
|
21.68
|
25.97
|
20.83
|
22.00
|
20.79
|
24.83
|
23.50
|
17.69
|
|
5
|
8.52
|
15.74
|
16.33
|
16.26
|
14.94
|
21.58
|
17.74
|
20.10
|
21.23
|
19.65
|
17.63
|
18.02
|
22.33
|
19.04
|
17.35
|
17.52
|
17.50
|
16.61
|
|
6
|
14.35
|
10.29
|
11.31
|
11.37
|
12.08
|
13.20
|
13.23
|
10.84
|
12.77
|
11.37
|
11.70
|
10.47
|
13.32
|
10.91
|
12.03
|
7.32
|
9.09
|
10.71
|
|
7
|
17.94
|
20.15
|
19.72
|
17.55
|
19.24
|
15.94
|
17.26
|
16.43
|
15.75
|
15.99
|
17.32
|
15.70
|
14.45
|
14.60
|
13.06
|
13.30
|
11.49
|
19.27
|
|
NA
|
4.04
|
3.53
|
2.51
|
3.17
|
2.23
|
1.93
|
2.26
|
1.05
|
2.65
|
1.35
|
0.78
|
1.36
|
1.88
|
1.85
|
1.55
|
1.55
|
1.20
|
5.81
|
Se observa que para las variables objetivo de impuestos,
ayuda a la pobreza y desempleo no existiría un sesgo
importante por parte de los grupos más desfavorecidos en educación,
ingresos y trabajo. Por tal motivo, esos casos perdidos pueden ser no
considerados en el análisis.
Se realiza un análisis de correspondencias múltiples para observar el
vínculo entre la variable de democracia y reducción de la
desigualdad. De este surge que los grupos más desfavorecidos son
los que menos reponden a dichas preguntas.

Se opta entonces por imputar a los casos sin respuesta en las
variables de democracia y reducción de la desigualdad,
utilizando la técnica de hot deck. Esta realiza una imputación
aleatoria, brindándole un valor válido a un caso con valor faltante.
Para ello, la imputación se hará al interior de los grupos de ingresos y
posteriormente, en el caso los grupos con ingresos faltantes, se
utilizará el nivel educativo.
Imputación variables objetivo
#1) Random Hot Deck para la variable democracia7 -----
lapop2004_2018$democracia7_imp <- lapop2004_2018$democracia7
set.seed(971986)
lapop2004_2018 <- lapop2004_2018 %>%
hotdeck(variable = "democracia7_imp",
domain_var = "ing_decil",
imp_suffix = "check")
print(lapop2004_2018 %>%
select(democracia7, democracia7_imp) %>%
summarytools::dfSummary(plain.ascii = FALSE,
style = "grid",
graph.magnif = 0.75,
valid.col = FALSE),
method = "render")
Data Frame Summary
lapop2004_2018
Dimensions: 66771 x 2
Duplicates: 66757
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
democracia7
[numeric] |
| Mean (sd) : 5.2 (1.7) | | min ≤ med ≤ max: | | 1 ≤ 5 ≤ 7 | | IQR (CV) : 3 (0.3) |
|
| 1 | : | 2556 | ( | 4.0% | ) | | 2 | : | 2328 | ( | 3.6% | ) | | 3 | : | 5070 | ( | 7.9% | ) | | 4 | : | 10045 | ( | 15.7% | ) | | 5 | : | 12021 | ( | 18.8% | ) | | 6 | : | 11202 | ( | 17.5% | ) | | 7 | : | 20796 | ( | 32.5% | ) |
|
 |
2753
(4.1%) |
| 2 |
democracia7_imp
[numeric] |
| Mean (sd) : 5.2 (1.7) | | min ≤ med ≤ max: | | 1 ≤ 5 ≤ 7 | | IQR (CV) : 3 (0.3) |
|
| 1 | : | 2677 | ( | 4.0% | ) | | 2 | : | 2427 | ( | 3.6% | ) | | 3 | : | 5305 | ( | 7.9% | ) | | 4 | : | 10497 | ( | 15.7% | ) | | 5 | : | 12569 | ( | 18.8% | ) | | 6 | : | 11666 | ( | 17.5% | ) | | 7 | : | 21630 | ( | 32.4% | ) |
|
 |
0
(0.0%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
#2) Random Hot Deck para la variable reduc_desigualdad -----
lapop2004_2018$reduc_desigualdad_imp <- lapop2004_2018$reduc_desigualdad
set.seed(971986)
lapop2004_2018 <- lapop2004_2018 %>%
hotdeck(variable = "reduc_desigualdad_imp",
domain_var = "ing_decil",
imp_suffix = "check")
print(lapop2004_2018 %>%
select(reduc_desigualdad, reduc_desigualdad_imp) %>%
summarytools::dfSummary(plain.ascii = FALSE,
style = "grid",
graph.magnif = 0.75,
valid.col = FALSE),
method = "render")
Data Frame Summary
lapop2004_2018
Dimensions: 66771 x 2
Duplicates: 66757
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
reduc_desigualdad
[numeric] |
| Mean (sd) : 5.7 (1.6) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 7 | | IQR (CV) : 2 (0.3) |
|
| 1 | : | 1931 | ( | 3.0% | ) | | 2 | : | 1659 | ( | 2.5% | ) | | 3 | : | 2978 | ( | 4.6% | ) | | 4 | : | 6419 | ( | 9.8% | ) | | 5 | : | 9795 | ( | 15.0% | ) | | 6 | : | 12511 | ( | 19.2% | ) | | 7 | : | 29897 | ( | 45.9% | ) |
|
 |
1581
(2.4%) |
| 2 |
reduc_desigualdad_imp
[numeric] |
| Mean (sd) : 5.7 (1.6) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 7 | | IQR (CV) : 2 (0.3) |
|
| 1 | : | 1975 | ( | 3.0% | ) | | 2 | : | 1698 | ( | 2.5% | ) | | 3 | : | 3048 | ( | 4.6% | ) | | 4 | : | 6553 | ( | 9.8% | ) | | 5 | : | 10030 | ( | 15.0% | ) | | 6 | : | 12816 | ( | 19.2% | ) | | 7 | : | 30651 | ( | 45.9% | ) |
|
 |
0
(0.0%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
Casos perdidos variables predictoras
print(lapop2004_2018 %>%
select(ideologia) %>%
summarytools::dfSummary(plain.ascii = FALSE,
style = "grid",
graph.magnif = 0.75,
valid.col = FALSE),
method = "render")
Data Frame Summary
lapop2004_2018
Dimensions: 66771 x 1
Duplicates: 66760
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
ideologia
[numeric] |
| Mean (sd) : 5.5 (2.5) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 10 | | IQR (CV) : 3 (0.4) |
|
| 1 | : | 4863 | ( | 8.6% | ) | | 2 | : | 2363 | ( | 4.2% | ) | | 3 | : | 5310 | ( | 9.3% | ) | | 4 | : | 4844 | ( | 8.5% | ) | | 5 | : | 7295 | ( | 12.8% | ) | | 6 | : | 14855 | ( | 26.1% | ) | | 7 | : | 5318 | ( | 9.4% | ) | | 8 | : | 4989 | ( | 8.8% | ) | | 9 | : | 2380 | ( | 4.2% | ) | | 10 | : | 4594 | ( | 8.1% | ) |
|
 |
9960
(14.9%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$wave,
useNA = "always"), margin = 2)*100, digits = 2),
format = "html", caption = "Ideología x onda") %>%
kable_styling()
Ideología x onda
|
|
2008
|
2010
|
2012
|
2014
|
2016
|
2018
|
NA
|
|
1
|
6.25
|
5.88
|
7.18
|
7.23
|
7.82
|
9.37
|
NaN
|
|
2
|
3.99
|
3.50
|
3.50
|
3.60
|
3.26
|
3.43
|
NaN
|
|
3
|
8.71
|
8.13
|
7.68
|
7.40
|
7.54
|
8.28
|
NaN
|
|
4
|
8.18
|
8.02
|
6.96
|
6.32
|
6.56
|
7.48
|
NaN
|
|
5
|
14.95
|
12.26
|
11.60
|
8.84
|
9.10
|
8.97
|
NaN
|
|
6
|
20.57
|
20.28
|
22.14
|
22.05
|
24.05
|
24.33
|
NaN
|
|
7
|
7.60
|
7.79
|
7.52
|
7.55
|
8.85
|
8.37
|
NaN
|
|
8
|
6.93
|
6.80
|
6.68
|
7.33
|
8.77
|
8.20
|
NaN
|
|
9
|
2.93
|
3.31
|
3.12
|
3.16
|
4.59
|
4.15
|
NaN
|
|
10
|
4.55
|
5.24
|
6.26
|
6.93
|
9.33
|
8.78
|
NaN
|
|
NA
|
15.32
|
18.79
|
17.36
|
19.59
|
10.14
|
8.64
|
NaN
|
kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$ing_decil,
useNA = "always"), margin = 2)*100, digits = 2),
format = "html", caption = "Ideología x ingreso") %>%
kable_styling()
Ideología x ingreso
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
NA
|
|
1
|
9.98
|
9.93
|
7.67
|
7.70
|
7.82
|
6.80
|
6.79
|
6.88
|
7.34
|
6.43
|
6.63
|
7.77
|
6.03
|
6.35
|
5.99
|
7.38
|
7.51
|
6.64
|
|
2
|
4.80
|
4.09
|
3.54
|
4.10
|
3.61
|
3.87
|
3.67
|
3.78
|
3.51
|
3.74
|
3.38
|
3.44
|
3.80
|
2.58
|
2.66
|
3.07
|
2.99
|
3.04
|
|
3
|
7.51
|
7.78
|
8.11
|
7.79
|
7.65
|
8.19
|
8.22
|
8.53
|
7.95
|
7.88
|
8.19
|
8.29
|
7.73
|
8.31
|
8.79
|
8.63
|
8.75
|
7.00
|
|
4
|
4.68
|
6.46
|
6.93
|
7.17
|
7.87
|
7.89
|
7.05
|
7.27
|
7.66
|
7.63
|
6.95
|
6.17
|
7.12
|
8.22
|
7.46
|
8.35
|
8.16
|
6.88
|
|
5
|
7.64
|
9.77
|
11.05
|
11.31
|
11.59
|
12.12
|
11.92
|
11.68
|
11.69
|
9.98
|
11.28
|
10.31
|
10.19
|
9.89
|
12.11
|
10.45
|
10.82
|
9.98
|
|
6
|
19.58
|
17.07
|
20.25
|
20.25
|
22.37
|
22.40
|
22.95
|
22.73
|
22.66
|
23.89
|
24.10
|
24.11
|
26.17
|
24.94
|
25.70
|
26.52
|
23.36
|
21.49
|
|
7
|
6.40
|
6.98
|
7.27
|
7.70
|
7.05
|
8.56
|
8.63
|
8.75
|
7.83
|
8.88
|
9.44
|
8.90
|
8.82
|
8.79
|
9.79
|
7.27
|
9.04
|
6.76
|
|
8
|
6.53
|
7.09
|
6.72
|
7.32
|
7.62
|
6.78
|
7.27
|
7.65
|
8.49
|
8.47
|
8.61
|
8.29
|
7.32
|
8.70
|
8.12
|
8.23
|
11.15
|
5.56
|
|
9
|
5.17
|
4.20
|
3.21
|
3.99
|
3.57
|
3.52
|
3.12
|
3.51
|
3.02
|
4.52
|
4.11
|
3.30
|
3.64
|
3.92
|
3.47
|
3.80
|
4.34
|
2.66
|
|
10
|
10.84
|
7.85
|
6.65
|
5.69
|
6.20
|
6.45
|
7.05
|
6.80
|
8.47
|
7.28
|
6.89
|
7.44
|
8.25
|
7.41
|
6.60
|
8.35
|
8.16
|
5.47
|
|
NA
|
16.87
|
18.77
|
18.61
|
16.97
|
14.65
|
13.43
|
13.32
|
12.42
|
11.37
|
11.30
|
10.42
|
12.01
|
10.92
|
10.89
|
9.31
|
7.95
|
5.72
|
24.52
|
kable(round(prop.table(table(lapop2004_2018$ideologia, lapop2004_2018$ed,
useNA = "always"), margin = 2)*100, digits = 2),
format = "html", caption = "Ideología x educacion") %>%
kable_styling()
Ideología x educacion
|
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
11
|
12
|
13
|
14
|
15
|
16
|
17
|
18
|
NA
|
|
1
|
16.00
|
14.91
|
14.19
|
13.14
|
11.63
|
12.54
|
8.78
|
7.48
|
6.96
|
7.32
|
6.27
|
6.50
|
4.94
|
4.53
|
4.48
|
4.44
|
4.22
|
4.94
|
5.35
|
10.57
|
|
2
|
4.31
|
5.40
|
5.48
|
5.73
|
4.90
|
5.22
|
4.08
|
3.83
|
3.65
|
3.73
|
2.82
|
3.47
|
2.47
|
3.38
|
2.06
|
3.00
|
2.92
|
3.23
|
2.54
|
3.22
|
|
3
|
8.04
|
7.51
|
7.58
|
8.27
|
8.76
|
9.62
|
8.22
|
7.78
|
7.72
|
8.56
|
6.81
|
8.18
|
6.80
|
6.97
|
8.16
|
7.89
|
8.46
|
7.76
|
9.16
|
6.90
|
|
4
|
5.89
|
6.22
|
5.56
|
6.74
|
6.72
|
7.01
|
6.32
|
7.59
|
5.73
|
7.00
|
7.21
|
7.54
|
7.02
|
8.26
|
8.53
|
8.05
|
9.17
|
8.36
|
8.03
|
6.90
|
|
5
|
7.46
|
7.28
|
9.60
|
8.27
|
8.63
|
9.28
|
9.79
|
9.68
|
9.61
|
9.42
|
10.69
|
11.90
|
11.80
|
12.17
|
13.84
|
12.53
|
14.10
|
12.79
|
11.17
|
9.89
|
|
6
|
11.77
|
14.20
|
13.47
|
16.44
|
15.08
|
14.91
|
19.14
|
20.01
|
20.49
|
21.43
|
23.35
|
23.53
|
26.91
|
28.57
|
27.38
|
25.80
|
25.80
|
24.53
|
25.28
|
16.09
|
|
7
|
2.49
|
3.29
|
4.52
|
5.40
|
6.86
|
6.25
|
7.48
|
7.37
|
7.43
|
8.05
|
8.54
|
8.53
|
8.22
|
8.17
|
8.66
|
8.96
|
9.79
|
10.81
|
11.77
|
7.59
|
|
8
|
3.57
|
4.11
|
5.16
|
4.49
|
5.99
|
5.19
|
7.44
|
6.90
|
7.75
|
8.47
|
7.92
|
7.46
|
7.54
|
7.42
|
8.70
|
8.75
|
8.67
|
9.10
|
11.64
|
5.06
|
|
9
|
3.32
|
3.52
|
3.47
|
2.63
|
2.32
|
3.19
|
3.90
|
3.10
|
3.65
|
3.92
|
3.55
|
4.02
|
3.24
|
3.20
|
3.75
|
3.78
|
3.83
|
3.09
|
4.01
|
3.45
|
|
10
|
7.88
|
6.34
|
5.89
|
6.12
|
6.99
|
6.01
|
7.98
|
7.16
|
7.96
|
8.32
|
7.16
|
6.80
|
6.37
|
6.13
|
5.01
|
6.61
|
6.43
|
6.70
|
5.69
|
9.20
|
|
NA
|
29.27
|
27.23
|
25.08
|
22.79
|
22.12
|
20.78
|
16.88
|
19.09
|
19.04
|
13.76
|
15.68
|
12.06
|
14.67
|
11.20
|
9.43
|
10.19
|
6.61
|
8.68
|
5.35
|
21.15
|
#MCA
lapop2004_2018$ed_f <- factor(lapop2004_2018$ed, labels = c(0:18))
lapop2004_2018$ing_decil_f <- factor(lapop2004_2018$ing_decil, labels = c(0:16))
lapop2004_2018$ideologia_f <- factor(lapop2004_2018$ideologia, labels = c(1:10))
variables_mca <- lapop2004_2018 %>%
select(ideologia_f, ed_f, categoria_ocup_f, ing_decil_f)
mca2 <- MCA(variables_mca, ncp = 2, graph = F)
ggcloud_variables(mca2, vlab = F, shapes = T, shapesize = 2, points = "besth")

Los casos perdidos en la variable ideología se encuentran
muy asociaciados al nivel educativo bajo y a los ingresos bajos.
Nuevamente, como en el caso de las variables objetivo, lo mejor sería
imputarlas según nivel económico, ya que está relacionada y no formará
parte del modelo de regresión.
Data Frame Summary
lapop2004_2018
Dimensions: 66771 x 2
Duplicates: 66751
| No |
Variable |
Stats / Values |
Freqs (% of Valid) |
Graph |
Missing |
| 1 |
ideologia
[numeric] |
| Mean (sd) : 5.5 (2.5) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 10 | | IQR (CV) : 3 (0.4) |
|
| 1 | : | 4863 | ( | 8.6% | ) | | 2 | : | 2363 | ( | 4.2% | ) | | 3 | : | 5310 | ( | 9.3% | ) | | 4 | : | 4844 | ( | 8.5% | ) | | 5 | : | 7295 | ( | 12.8% | ) | | 6 | : | 14855 | ( | 26.1% | ) | | 7 | : | 5318 | ( | 9.4% | ) | | 8 | : | 4989 | ( | 8.8% | ) | | 9 | : | 2380 | ( | 4.2% | ) | | 10 | : | 4594 | ( | 8.1% | ) |
|
 |
9960
(14.9%) |
| 2 |
ideologia_imp
[numeric] |
| Mean (sd) : 5.5 (2.5) | | min ≤ med ≤ max: | | 1 ≤ 6 ≤ 10 | | IQR (CV) : 3 (0.4) |
|
| 1 | : | 5750 | ( | 8.6% | ) | | 2 | : | 2791 | ( | 4.2% | ) | | 3 | : | 6201 | ( | 9.3% | ) | | 4 | : | 5663 | ( | 8.5% | ) | | 5 | : | 8572 | ( | 12.8% | ) | | 6 | : | 17539 | ( | 26.3% | ) | | 7 | : | 6271 | ( | 9.4% | ) | | 8 | : | 5780 | ( | 8.7% | ) | | 9 | : | 2795 | ( | 4.2% | ) | | 10 | : | 5409 | ( | 8.1% | ) |
|
 |
0
(0.0%) |
Generated by summarytools 1.0.1 (R version 4.2.1)
2023-01-10
Problema variable Tranferencias Condicionadas
Ayuda gobierno x Transferencias condicionadas. Chile 2016.
|
wf1
|
1
|
2
|
NA
|
Total
|
|
1
|
35.5%
|
8.7%
|
25.0%
|
11.7%
|
|
2
|
64.5%
|
91.0%
|
59.1%
|
87.7%
|
|
NA
|
|
0.2%
|
15.9%
|
0.6%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
Ayuda gobierno x Transferencias condicionadas. Todos los países 2016.
|
wf1
|
1
|
2
|
NA
|
Total
|
|
1
|
36.4%
|
5.5%
|
19.2%
|
12.0%
|
|
2
|
63.1%
|
94.3%
|
68.0%
|
87.6%
|
|
NA
|
0.6%
|
0.2%
|
12.8%
|
0.4%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
Las variables de Ayuda económica del gobierno y
Transferencias condicionadas parecieran no apuntar a lo mismo.
Del total de familias que recibió transferencias condicionadas, solo un
35,5% indicó declarar que recibió ayuda económica del gobierno.
Descriptivos
Tablas resumen
| Característica |
2008, N = 10,573 |
2010, N = 11,925 |
2012, N = 10,666 |
2014, N = 10,626 |
2016, N = 11,972 |
2018, N = 11,009 |
Total |
| Acuerdo con democracia |
5.45 (1.64) |
5.39 (1.66) |
5.41 (1.62) |
5.37 (1.66) |
4.87 (1.77) |
5.00 (1.68) |
5.24 (1.69) |
| Acuerdo con políticas de
reducción de desigualdad |
5.97 (1.43) |
5.98 (1.40) |
5.93 (1.38) |
5.68 (1.61) |
5.46 (1.73) |
5.34 (1.73) |
5.72 (1.58) |
| Voto pasado |
8,233 (78.5%) |
7,824 (79.8%) |
8,519 (80.4%) |
8,002 (75.9%) |
9,060 (76.0%) |
8,300 (75.6%) |
49,938 (77.6%) |
| Voto presente |
7,120 (84.0%) |
6,275 (88.7%) |
7,675 (87.1%) |
7,765 (86.1%) |
9,607 (86.2%) |
9,042 (87.9%) |
47,484 (86.6%) |
| Desempleo como fenómeno voluntario |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
3.44 (2.00) |
3.44 (2.00) |
| Los gobiernos deben invertir en ayudar
a los pobres |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
5.53 (1.75) |
5.53 (1.75) |
| Injusto que los ricos paguen altos
impuestos |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
NA (NA) |
4.29 (1.90) |
4.29 (1.90) |
| Generalización corrupción |
2,001 (20.2%) |
2,282 (20.1%) |
1,908 (19.0%) |
1,244 (17.1%) |
625 (24.0%) |
1,463 (27.4%) |
9,523 (20.5%) |
| Golpe militar por corrupción |
3,104 (53.4%) |
6,962 (61.3%) |
6,334 (61.9%) |
6,053 (60.1%) |
3,037 (61.6%) |
3,442 (65.6%) |
28,932 (60.7%) |
| Aprobación de cierre del congreso |
0 (NA%) |
9,434 (86.2%) |
8,504 (86.8%) |
8,077 (83.6%) |
8,823 (79.2%) |
4,421 (75.1%) |
39,259 (82.8%) |
| Aprobación de cierre de la corte |
0 (NA%) |
9,681 (89.2%) |
8,696 (89.2%) |
0 (NA%) |
0 (NA%) |
4,114 (71.4%) |
22,491 (85.3%) |
| Simpatía por partido político |
2,990 (28.9%) |
3,530 (30.2%) |
3,044 (29.0%) |
2,942 (28.1%) |
2,523 (21.2%) |
2,522 (23.0%) |
17,551 (26.7%) |
| Categoría ocupacional |
|
|
|
|
|
|
|
| Patrón |
216 (2.1%) |
201 (1.7%) |
165 (1.6%) |
149 (1.4%) |
258 (2.2%) |
260 (2.4%) |
1,249 (1.9%) |
| Asalariado público |
801 (7.7%) |
878 (7.4%) |
815 (7.7%) |
732 (6.9%) |
878 (7.4%) |
765 (7.0%) |
4,869 (7.4%) |
| Asalariado privado |
2,394 (22.9%) |
2,514 (21.3%) |
2,490 (23.5%) |
2,407 (22.8%) |
2,156 (18.2%) |
2,086 (19.2%) |
14,047 (21.2%) |
| Cuenta propia |
2,192 (21.0%) |
2,765 (23.4%) |
2,513 (23.7%) |
2,509 (23.8%) |
2,836 (23.9%) |
2,333 (21.5%) |
15,148 (22.9%) |
| Desocupado |
640 (6.1%) |
943 (8.0%) |
619 (5.8%) |
504 (4.8%) |
1,339 (11.3%) |
1,232 (11.3%) |
5,277 (8.0%) |
| Inactivo |
4,199 (40.2%) |
4,509 (38.2%) |
3,981 (37.6%) |
4,258 (40.3%) |
4,398 (37.1%) |
4,198 (38.6%) |
25,543 (38.6%) |
| Formalidad |
|
|
|
|
|
|
|
| Formal |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
2,954 (27.0%) |
2,954 (27.0%) |
| Informal |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
2,649 (24.2%) |
2,649 (24.2%) |
| Desocupado |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
1,132 (10.4%) |
1,132 (10.4%) |
| Inactivo |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
4,198 (38.4%) |
4,198 (38.4%) |
| Estatus ocupacional |
|
|
|
|
|
|
|
| Directivos-Profesionales |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
471 (4.5%) |
471 (4.5%) |
| Técnicos-administrativos-vendedores |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
631 (6.0%) |
631 (6.0%) |
| Trabajadores manuales calificados |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
2,678 (25.7%) |
2,678 (25.7%) |
| Trabajadores manuales no calificados |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
1,316 (12.6%) |
1,316 (12.6%) |
| No ocupados |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
5,337 (51.2%) |
5,337 (51.2%) |
| Ideología (der-izq) |
5.36 (2.32) |
5.45 (2.36) |
5.50 (2.42) |
5.58 (2.49) |
5.76 (2.54) |
5.60 (2.57) |
5.54 (2.46) |
| Sexo |
|
|
|
|
|
|
|
| Varón |
5,008 (47.4%) |
5,610 (47.0%) |
5,097 (47.8%) |
4,975 (46.8%) |
5,945 (49.7%) |
5,455 (49.6%) |
32,090 (48.1%) |
| Mujer |
5,565 (52.6%) |
6,315 (53.0%) |
5,569 (52.2%) |
5,651 (53.2%) |
6,026 (50.3%) |
5,552 (50.4%) |
34,678 (51.9%) |
| Edad |
41 (16) |
40 (17) |
41 (16) |
42 (17) |
41 (16) |
42 (17) |
41 (17) |
| Años educativos |
9.3 (4.3) |
9.6 (4.2) |
9.8 (4.1) |
9.8 (4.1) |
10.2 (4.0) |
10.4 (4.1) |
9.9 (4.2) |
| Región |
|
|
|
|
|
|
|
| 1 |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
9,291 (84.4%) |
9,291 (84.4%) |
| 2 |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
0 (NA%) |
1,718 (15.6%) |
1,718 (15.6%) |
| Nivel de desempleo |
7.14 (1.80) |
7.56 (2.03) |
6.32 (1.48) |
6.32 (1.34) |
6.98 (2.35) |
7.77 (2.85) |
7.03 (2.12) |
| Nivel de informalidad |
46 (14) |
45 (13) |
43 (14) |
43 (14) |
45 (14) |
43 (13) |
44 (14) |
| Nivel de empleo público |
11.1 (3.4) |
11.4 (3.5) |
11.5 (4.0) |
11.4 (4.0) |
11.2 (4.2) |
11.4 (4.4) |
11.3 (3.9) |
| Brecha informales / asalariados reg. |
50.3 (6.7) |
51.6 (7.7) |
50.6 (7.2) |
50.6 (6.4) |
50.0 (5.3) |
49.9 (5.9) |
50.5 (6.6) |
| País |
|
|
|
|
|
|
|
| Argentina |
1,486 (14.1%) |
1,410 (11.8%) |
1,512 (14.2%) |
1,512 (14.2%) |
1,528 (12.8%) |
1,528 (13.9%) |
8,976 (13.4%) |
| Brasil |
1,497 (14.2%) |
2,482 (20.8%) |
1,499 (14.1%) |
1,500 (14.1%) |
1,532 (12.8%) |
1,498 (13.6%) |
10,008 (15.0%) |
| Chile |
1,527 (14.4%) |
1,965 (16.5%) |
1,571 (14.7%) |
1,571 (14.8%) |
1,625 (13.6%) |
1,638 (14.9%) |
9,897 (14.8%) |
| Colombia |
1,503 (14.2%) |
1,506 (12.6%) |
1,512 (14.2%) |
1,496 (14.1%) |
1,563 (13.1%) |
1,663 (15.1%) |
9,243 (13.8%) |
| México |
1,560 (14.8%) |
1,562 (13.1%) |
1,560 (14.6%) |
1,535 (14.4%) |
1,563 (13.1%) |
1,580 (14.4%) |
9,360 (14.0%) |
| Perú |
1,500 (14.2%) |
1,500 (12.6%) |
1,500 (14.1%) |
1,500 (14.1%) |
2,647 (22.1%) |
1,521 (13.8%) |
10,168 (15.2%) |
| Uruguay |
1,500 (14.2%) |
1,500 (12.6%) |
1,512 (14.2%) |
1,512 (14.2%) |
1,514 (12.6%) |
1,581 (14.4%) |
9,119 (13.7%) |
Descriptivos variables independientes


Cruces variable laboral y variables objetivo 2008-2018

|
democracia7
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
|
1
|
4.5%
|
2.8%
|
3.3%
|
4.4%
|
5.1%
|
4.0%
|
|
2
|
3.7%
|
2.9%
|
2.9%
|
4.1%
|
4.3%
|
3.8%
|
|
3
|
7.6%
|
6.5%
|
6.9%
|
8.5%
|
9.5%
|
8.1%
|
|
4
|
13.6%
|
13.1%
|
15.2%
|
16.5%
|
18.9%
|
15.4%
|
|
5
|
15.7%
|
16.7%
|
18.1%
|
19.2%
|
21.2%
|
18.9%
|
|
6
|
16.7%
|
17.5%
|
17.9%
|
17.3%
|
15.7%
|
17.9%
|
|
7
|
38.2%
|
40.7%
|
35.6%
|
30.1%
|
25.3%
|
31.9%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|

|
reduc_desigualdad
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
|
1
|
4.2%
|
2.4%
|
2.4%
|
3.2%
|
3.1%
|
3.1%
|
|
2
|
2.7%
|
1.9%
|
2.2%
|
3.0%
|
2.4%
|
2.6%
|
|
3
|
5.5%
|
3.8%
|
4.2%
|
4.7%
|
4.7%
|
4.8%
|
|
4
|
11.0%
|
8.8%
|
9.4%
|
10.4%
|
9.2%
|
10.0%
|
|
5
|
15.1%
|
14.3%
|
15.3%
|
15.0%
|
14.5%
|
15.1%
|
|
6
|
20.4%
|
20.4%
|
19.2%
|
19.2%
|
18.3%
|
19.2%
|
|
7
|
41.2%
|
48.4%
|
47.3%
|
44.6%
|
47.7%
|
45.2%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
|
voto_pasado
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
|
0
|
18.7%
|
11.2%
|
21.7%
|
19.6%
|
29.3%
|
25.3%
|
|
1
|
81.3%
|
88.8%
|
78.3%
|
80.4%
|
70.7%
|
74.7%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
|
voto_presente
|
Patrón
|
Asalariado público
|
Asalariado privado
|
Cuenta propia
|
Desocupado
|
Inactivo
|
|
0
|
11.4%
|
7.9%
|
13.9%
|
12.1%
|
14.0%
|
14.8%
|
|
1
|
88.6%
|
92.1%
|
86.1%
|
87.9%
|
86.0%
|
85.2%
|
|
Total
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
100.0%
|
Modelos Multinivel 2008-2018
El ICC para la variable objetivo de acuerdo con
la democracia es de 0.095, 0.095, 0.095.
El ICC para la variable objetivo de reducción de
la desigualdad es de 0.04, 0.04, 0.04.
El ICC para la variable objetivo de voto
pasado es de 0.11, 0.11, 0.11.
El ICC para la variable objetivo de voto
presente es de 0.135, 0.135, 0.135.
Multinivel democracia
|
|
Ind
|
Ind + grup
|
Ind + grup + int
|
Random_apub
|
Random_apri
|
Random_cuent
|
Random_desoc
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
Intercepto
|
5.26 ***
|
5.25 ***
|
5.25 ***
|
5.25 ***
|
5.25 ***
|
5.25 ***
|
5.25 ***
|
|
Patrón
|
0.00
|
0.00
|
0.00
|
0.00
|
0.00
|
0.00
|
0.00
|
|
Asalariado pub.
|
0.06 *
|
0.06 *
|
0.06 *
|
0.06
|
0.06 *
|
0.06 *
|
0.06 *
|
|
Asalariado priv.
|
0.05 **
|
0.05 **
|
0.05 **
|
0.05 **
|
0.05 *
|
0.05 **
|
0.05 **
|
|
Cuenta propia
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
|
Desocupado
|
-0.11 ***
|
-0.11 ***
|
-0.10 ***
|
-0.10 ***
|
-0.10 ***
|
-0.10 ***
|
-0.10 ***
|
|
Ideología (der-izq)
|
-0.02 ***
|
-0.02 ***
|
-0.02 ***
|
-0.02 ***
|
-0.02 ***
|
-0.02 ***
|
-0.02 ***
|
|
Varón
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
|
Edad
|
0.01 ***
|
0.01 ***
|
0.01 ***
|
0.01 ***
|
0.01 ***
|
0.01 ***
|
0.01 ***
|
|
Años educ.
|
0.06 ***
|
0.06 ***
|
0.06 ***
|
0.06 ***
|
0.06 ***
|
0.06 ***
|
0.06 ***
|
|
Desempleo
|
|
-0.02
|
-0.02
|
-0.01
|
-0.02
|
-0.04
|
-0.02
|
|
Informalidad
|
|
-0.03 ***
|
-0.03 ***
|
-0.04 ***
|
-0.03 ***
|
-0.03 ***
|
-0.03 ***
|
|
Empleo pub.
|
|
0.04
|
0.04
|
0.05 **
|
0.05 *
|
0.05 **
|
0.04 *
|
|
Brecha remun.
|
|
-0.05 ***
|
-0.05 ***
|
-0.06 ***
|
-0.05 ***
|
-0.05 ***
|
-0.05 ***
|
|
Desocupado*desempleo
|
|
|
-0.03 **
|
-0.03 **
|
-0.03 **
|
-0.03 *
|
-0.03 *
|
|
Random Effects
|
|
σ2
|
2.50
|
2.50
|
2.50
|
2.50
|
2.50
|
2.50
|
2.50
|
|
τ00
|
0.27 pais_anio
|
0.11 pais_anio
|
0.11 pais_anio
|
0.12 pais_anio
|
0.12 pais_anio
|
0.12 pais_anio
|
0.11 pais_anio
|
|
τ11
|
|
|
|
0.02 pais_anio.asal_pub_cwc
|
0.01 pais_anio.asal_pri_cwc
|
0.00 pais_anio.cuenta_prop_cwc
|
0.00 pais_anio.desocupado_cwc
|
|
ρ01
|
|
|
|
-0.68 pais_anio
|
-0.42 pais_anio
|
0.75 pais_anio
|
0.88 pais_anio
|
|
N
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
|
Observations
|
62060
|
62060
|
62060
|
62060
|
62060
|
62060
|
62060
|
|
Marginal R2 / Conditional R2
|
0.026 / 0.119
|
0.078 / 0.119
|
0.079 / 0.119
|
0.096 / 0.137
|
0.081 / 0.122
|
0.086 / 0.127
|
0.081 / 0.122
|
|
AIC
|
233260.653
|
233262.044
|
233264.387
|
233249.188
|
233259.700
|
233264.016
|
233267.221
|
- p<0.05 ** p<0.01 *** p<0.001
|
## Data: base_ml
## Models:
## democracia_null: democracia7 ~ 1 + (1 | pais_anio)
## democracia_ind: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## democracia_null 3 234949 234976 -117472 234943
## democracia_ind 12 233188 233296 -116582 233164 1779.5 9 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## democracia_ind: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## democracia_ind 12 233188 233296 -116582 233164
## democracia_ind_grup 16 233161 233305 -116564 233129 34.879 4 4.92e-07
##
## democracia_ind
## democracia_ind_grup ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## democracia_ind_grup: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## democracia_ind_grup_int: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## democracia_ind_grup 16 233161 233305 -116564 233129
## democracia_ind_grup_int 17 233156 233309 -116561 233122 6.9751 1
## Pr(>Chisq)
## democracia_ind_grup
## democracia_ind_grup_int 0.008265 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## democracia_ind_grup_int: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## democracia_random_apub: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pub_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## democracia_ind_grup_int 17 233156 233309 -116561 233122
## democracia_random_apub 19 233140 233312 -116551 233102 19.468 2
## Pr(>Chisq)
## democracia_ind_grup_int
## democracia_random_apub 5.922e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## democracia_ind_grup_int: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## democracia_random_apri: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pri_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## democracia_ind_grup_int 17 233156 233309 -116561 233122
## democracia_random_apri 19 233151 233323 -116557 233113 8.463 2 0.01453
##
## democracia_ind_grup_int
## democracia_random_apri *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## democracia_ind_grup_int: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## democracia_random_cuent: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + cuenta_prop_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## democracia_ind_grup_int 17 233156 233309 -116561 233122
## democracia_random_cuent 19 233155 233327 -116559 233117 4.5617 2
## Pr(>Chisq)
## democracia_ind_grup_int
## democracia_random_cuent 0.1022
## Data: base_ml
## Models:
## democracia_ind_grup_int: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## democracia_random_desoc: democracia7 ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + desocupado_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## democracia_ind_grup_int 17 233156 233309 -116561 233122
## democracia_random_desoc 19 233159 233330 -116560 233121 1.2147 2
## Pr(>Chisq)
## democracia_ind_grup_int
## democracia_random_desoc 0.5448
Importante
El test de devianza muestra que los modelos de pendiente aleatoria para
los cuentapropia y para desocupados no
mejoran el ajuste. El pseudo r2 para el segundo nivel (países años)
- en el modelo con predictores individuales es de
0.0237799,
- en el modelo de predictores individuales y grupales es de
0.578056,
- en el modelo con interacciones es de
0.5780539,
- en el los modelos de pendiente aleatoria es de
0.5587182.

Multinivel reducción desigualdad
|
|
Ind
|
Ind + grup
|
Random_apub
|
Random_apri
|
Random_cuent
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
(Intercept)
|
5.73 ***
|
5.73 ***
|
5.73 ***
|
5.73 ***
|
5.73 ***
|
|
patron_cwc
|
-0.09
|
-0.09
|
-0.09
|
-0.09
|
-0.09
|
|
asal_pub_cwc
|
0.14 ***
|
0.14 ***
|
0.14 ***
|
0.14 ***
|
0.14 ***
|
|
asal_pri_cwc
|
0.05 **
|
0.05 **
|
0.05 **
|
0.05 *
|
0.05 **
|
|
cuenta_prop_cwc
|
0.02
|
0.02
|
0.02
|
0.02
|
0.01
|
|
desocupado_cwc
|
0.13 ***
|
0.13 ***
|
0.13 ***
|
0.13 ***
|
0.13 ***
|
|
ideologia_cwc
|
0.02 ***
|
0.02 ***
|
0.02 ***
|
0.02 ***
|
0.02 ***
|
|
sexo_cwc
|
-0.00
|
-0.00
|
-0.00
|
-0.00
|
-0.00
|
|
edad_cwc
|
0.00
|
0.00
|
0.00
|
0.00
|
0.00
|
|
educ_cwc
|
0.00 **
|
0.00 **
|
0.00 **
|
0.00 **
|
0.00 **
|
|
desempleo_cgm
|
|
0.01
|
0.01
|
0.00
|
0.01
|
|
informalidad_cgm
|
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
|
empleo_pub_cgm
|
|
-0.01
|
-0.00
|
-0.01
|
-0.01
|
|
brecha_remun_cgm
|
|
0.00
|
-0.00
|
-0.00
|
0.00
|
|
Random Effects
|
|
σ2
|
2.36
|
2.36
|
2.36
|
2.36
|
2.36
|
|
τ00
|
0.10 pais_anio
|
0.08 pais_anio
|
0.08 pais_anio
|
0.08 pais_anio
|
0.08 pais_anio
|
|
τ11
|
|
|
0.01 pais_anio.asal_pub_cwc
|
0.01 pais_anio.asal_pri_cwc
|
0.01 pais_anio.cuenta_prop_cwc
|
|
ρ01
|
|
|
-0.42 pais_anio
|
-0.38 pais_anio
|
-0.15 pais_anio
|
|
N
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
|
Observations
|
62060
|
62060
|
62060
|
62060
|
62060
|
|
Marginal R2 / Conditional R2
|
0.002 / 0.041
|
0.009 / 0.042
|
0.008 / 0.041
|
0.009 / 0.042
|
0.009 / 0.042
|
|
AIC
|
229750.915
|
229780.297
|
229779.286
|
229776.220
|
229771.810
|
- p<0.05 ** p<0.01 *** p<0.001
|
## Data: base_ml
## Models:
## reduc_desigualdad_null: reduc_desigualdad ~ 1 + (1 | pais_anio)
## reduc_desigualdad_ind: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## reduc_desigualdad_null 3 229809 229836 -114902 229803
## reduc_desigualdad_ind 12 229676 229785 -114826 229652 150.72 9 < 2.2e-16
##
## reduc_desigualdad_null
## reduc_desigualdad_ind ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## reduc_desigualdad_ind: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## reduc_desigualdad_ind_grup: reduc_desigualdad ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## reduc_desigualdad_ind 12 229676 229785 -114826 229652
## reduc_desigualdad_ind_grup 16 229677 229821 -114822 229645 7.6622 4
## Pr(>Chisq)
## reduc_desigualdad_ind
## reduc_desigualdad_ind_grup 0.1048
Importante
Para la variable objetivo reducción de la desigualdad la prueba
de devianza muestra que el modelo con variables contextuales agregadas
no mejora el ajuste por sobre el modelo de variables individuales.

Multinivel voto pasado
|
|
Ind
|
Ind + grup
|
voto_pasado_ind_grup_int
|
Random_apub
|
Random_apri
|
Random_cuent
|
|
Predictors
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
|
Intercepto
|
4.88 ***
|
4.88 ***
|
4.88 ***
|
4.90 ***
|
4.90 ***
|
4.89 ***
|
|
Patrón
|
1.72 ***
|
1.72 ***
|
1.72 ***
|
1.72 ***
|
1.73 ***
|
1.71 ***
|
|
Asalariado pub.
|
2.70 ***
|
2.70 ***
|
2.70 ***
|
2.78 ***
|
2.71 ***
|
2.70 ***
|
|
Asalariado priv.
|
1.85 ***
|
1.85 ***
|
1.85 ***
|
1.85 ***
|
1.97 ***
|
1.85 ***
|
|
Cuenta propia
|
1.75 ***
|
1.75 ***
|
1.75 ***
|
1.74 ***
|
1.75 ***
|
1.80 ***
|
|
Desocupado
|
1.32 ***
|
1.32 ***
|
1.30 ***
|
1.30 ***
|
1.31 ***
|
1.30 ***
|
|
Ideología (der-izq)
|
0.98 ***
|
0.98 ***
|
0.98 ***
|
0.98 ***
|
0.98 ***
|
0.98 ***
|
|
Varón
|
0.69 ***
|
0.69 ***
|
0.69 ***
|
0.70 ***
|
0.70 ***
|
0.70 ***
|
|
Edad
|
1.06 ***
|
1.06 ***
|
1.06 ***
|
1.06 ***
|
1.06 ***
|
1.06 ***
|
|
Años educ.
|
1.07 ***
|
1.07 ***
|
1.07 ***
|
1.07 ***
|
1.07 ***
|
1.07 ***
|
|
Desempleo
|
|
0.97
|
0.97
|
0.97
|
0.90
|
0.94
|
|
Informalidad
|
|
1.01
|
1.01
|
1.01
|
1.00
|
1.01
|
|
Empleo pub.
|
|
1.13 ***
|
1.13 ***
|
1.11 *
|
1.04
|
1.11 **
|
|
Brecha remun.
|
|
0.99
|
0.99
|
1.00
|
1.01
|
1.00
|
|
Desocupado*desempleo
|
|
|
1.03
|
1.03
|
1.03
|
1.03
|
|
Random Effects
|
|
σ2
|
3.29
|
3.29
|
3.29
|
3.29
|
3.29
|
3.29
|
|
τ00
|
0.51 pais_anio
|
0.36 pais_anio
|
0.36 pais_anio
|
0.37 pais_anio
|
0.42 pais_anio
|
0.37 pais_anio
|
|
τ11
|
|
|
|
0.07 pais_anio.asal_pub_cwc
|
0.05 pais_anio.asal_pri_cwc
|
0.03 pais_anio.cuenta_prop_cwc
|
|
ρ01
|
|
|
|
0.28 pais_anio
|
0.72 pais_anio
|
0.53 pais_anio
|
|
N
|
41 pais_anio
|
41 pais_anio
|
41 pais_anio
|
41 pais_anio
|
41 pais_anio
|
41 pais_anio
|
|
Observations
|
59838
|
59838
|
59838
|
59838
|
59838
|
59838
|
|
Marginal R2 / Conditional R2
|
0.193 / 0.302
|
0.224 / 0.301
|
0.224 / 0.301
|
0.217 / 0.298
|
0.210 / 0.302
|
0.221 / 0.301
|
|
AIC
|
52839.459
|
52833.453
|
52832.740
|
52832.546
|
52796.952
|
52821.154
|
- p<0.05 ** p<0.01 *** p<0.001
|
## Data: base_ml
## Models:
## voto_pasado_null: voto_pasado ~ 1 + (1 | pais_anio)
## voto_pasado_ind: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_null 2 59703 59721 -29849 59699
## voto_pasado_ind 11 52839 52938 -26409 52817 6881.3 9 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_pasado_ind: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## voto_pasado_ind_grup: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind 11 52839 52938 -26409 52817
## voto_pasado_ind_grup 15 52833 52968 -26402 52803 14.007 4 0.007274 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_pasado_ind_grup: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## voto_pasado_ind_grup_int: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind_grup 15 52833 52968 -26402 52803
## voto_pasado_ind_grup_int 16 52833 52977 -26400 52801 2.7132 1 0.09952
##
## voto_pasado_ind_grup
## voto_pasado_ind_grup_int .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_pasado_ind_grup_int: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_pasado_random_apub: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pub_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind_grup_int 16 52833 52977 -26400 52801
## voto_pasado_random_apub 18 52833 52995 -26398 52797 4.1936 2 0.1228
## Data: base_ml
## Models:
## voto_pasado_ind_grup_int: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_pasado_random_apri: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pri_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind_grup_int 16 52833 52977 -26400 52801
## voto_pasado_random_apri 18 52797 52959 -26381 52761 39.787 2 2.292e-09
##
## voto_pasado_ind_grup_int
## voto_pasado_random_apri ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_pasado_ind_grup_int: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_pasado_random_cuent: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + cuenta_prop_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind_grup_int 16 52833 52977 -26400 52801
## voto_pasado_random_cuent 18 52821 52983 -26393 52785 15.586 2 0.0004127
##
## voto_pasado_ind_grup_int
## voto_pasado_random_cuent ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_pasado_ind_grup_int: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_pasado_random_desoc: voto_pasado ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + desocupado_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_pasado_ind_grup_int 16 52833 52977 -26400 52801
## voto_pasado_random_desoc 18 52833 52995 -26398 52797 4.0092 2 0.1347

Multinivel voto presente
|
|
Ind
|
Ind + grup
|
Ind + grup + int
|
Random_apub
|
Random_apri
|
Random_cuent
|
|
Predictors
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
|
Intercepto
|
8.09 ***
|
7.87 ***
|
7.87 ***
|
7.91 ***
|
7.93 ***
|
7.83 ***
|
|
Patrón
|
1.11
|
1.11
|
1.11
|
1.11
|
1.12
|
1.11
|
|
Asalariado pub.
|
1.58 ***
|
1.58 ***
|
1.58 ***
|
1.66 ***
|
1.60 ***
|
1.58 ***
|
|
Asalariado priv.
|
1.10 *
|
1.10 *
|
1.10 *
|
1.10 *
|
1.18 **
|
1.10 *
|
|
Cuenta propia
|
1.20 ***
|
1.20 ***
|
1.20 ***
|
1.20 ***
|
1.21 ***
|
1.23 ***
|
|
Desocupado
|
1.12 *
|
1.12 *
|
1.17 **
|
1.17 **
|
1.18 **
|
1.17 **
|
|
Ideología (der-izq)
|
0.96 ***
|
0.96 ***
|
0.96 ***
|
0.96 ***
|
0.96 ***
|
0.96 ***
|
|
Varón
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
1.00
|
|
Edad
|
1.01 ***
|
1.01 ***
|
1.01 ***
|
1.01 ***
|
1.01 ***
|
1.01 ***
|
|
Años educ.
|
1.04 ***
|
1.04 ***
|
1.04 ***
|
1.04 ***
|
1.04 ***
|
1.04 ***
|
|
Desempleo
|
|
0.94
|
0.94
|
0.94
|
0.94
|
0.90
|
|
Informalidad
|
|
1.02
|
1.02
|
1.02
|
1.02
|
1.02
|
|
Empleo pub.
|
|
1.12 **
|
1.12 **
|
1.13 **
|
1.10 *
|
1.12 **
|
|
Brecha remun.
|
|
0.99
|
0.99
|
0.99
|
0.99
|
0.98
|
|
Desocupado*desempleo
|
|
|
0.94 *
|
0.94 **
|
0.94 **
|
0.95 *
|
|
Random Effects
|
|
σ2
|
3.29
|
3.29
|
3.29
|
3.29
|
3.29
|
3.29
|
|
τ00
|
0.52 pais_anio
|
0.39 pais_anio
|
0.39 pais_anio
|
0.39 pais_anio
|
0.39 pais_anio
|
0.40 pais_anio
|
|
τ11
|
|
|
|
0.14 pais_anio.asal_pub_cwc
|
0.07 pais_anio.asal_pri_cwc
|
0.03 pais_anio.cuenta_prop_cwc
|
|
ρ01
|
|
|
|
-0.02 pais_anio
|
0.30 pais_anio
|
0.44 pais_anio
|
|
N
|
40 pais_anio
|
40 pais_anio
|
40 pais_anio
|
40 pais_anio
|
40 pais_anio
|
40 pais_anio
|
|
Observations
|
51598
|
51598
|
51598
|
51598
|
51598
|
51598
|
|
Marginal R2 / Conditional R2
|
0.017 / 0.152
|
0.050 / 0.150
|
0.050 / 0.151
|
0.052 / 0.155
|
0.043 / 0.148
|
0.062 / 0.165
|
|
AIC
|
36839.186
|
36835.915
|
36831.263
|
36823.411
|
36815.046
|
36826.468
|
- p<0.05 ** p<0.01 *** p<0.001
|
## Data: base_ml
## Models:
## voto_presente_null: voto_presente ~ 1 + (1 | pais_anio)
## voto_presente_ind: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_presente_null 2 37147 37165 -18572 37143
## voto_presente_ind 11 36839 36937 -18409 36817 325.99 9 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## voto_presente_ind_grup: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## voto_presente_ind 11 36839 36937 -18409 36817
## voto_presente_ind_grup 15 36836 36969 -18403 36806 11.271 4 0.02368 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind_grup: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## voto_presente_ind_grup_int: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## voto_presente_ind_grup 15 36836 36969 -18403 36806
## voto_presente_ind_grup_int 16 36831 36973 -18400 36799 6.6519 1
## Pr(>Chisq)
## voto_presente_ind_grup
## voto_presente_ind_grup_int 0.009905 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind_grup_int: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_presente_random_apub: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pub_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## voto_presente_ind_grup_int 16 36831 36973 -18400 36799
## voto_presente_random_apub 18 36823 36983 -18394 36787 11.851 2
## Pr(>Chisq)
## voto_presente_ind_grup_int
## voto_presente_random_apub 0.00267 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind_grup_int: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_presente_random_apri: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pri_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## voto_presente_ind_grup_int 16 36831 36973 -18400 36799
## voto_presente_random_apri 18 36815 36974 -18390 36779 20.216 2
## Pr(>Chisq)
## voto_presente_ind_grup_int
## voto_presente_random_apri 4.074e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind_grup_int: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_presente_random_cuent: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + cuenta_prop_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## voto_presente_ind_grup_int 16 36831 36973 -18400 36799
## voto_presente_random_cuent 18 36826 36986 -18395 36790 8.7948 2
## Pr(>Chisq)
## voto_presente_ind_grup_int
## voto_presente_random_cuent 0.01231 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## voto_presente_ind_grup_int: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## voto_presente_random_desoc: voto_presente ~ patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + ideologia_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + desocupado_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df
## voto_presente_ind_grup_int 16 36831 36973 -18400 36799
## voto_presente_random_desoc 18 36827 36986 -18395 36791 8.6252 2
## Pr(>Chisq)
## voto_presente_ind_grup_int
## voto_presente_random_desoc 0.0134 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multinivel ideología
|
|
Ind
|
Ind + grup
|
Ind + grup + int
|
Random_apub
|
Random_apri
|
Random_cuent
|
Random_desoc
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
Intercepto
|
5.54 ***
|
5.53 ***
|
5.53 ***
|
5.53 ***
|
5.53 ***
|
5.53 ***
|
5.53 ***
|
|
Patrón
|
-0.14
|
-0.14
|
-0.14
|
-0.14
|
-0.14
|
-0.14
|
-0.14
|
|
Asalariado pub.
|
0.10 *
|
0.10 *
|
0.09 *
|
0.09
|
0.10 *
|
0.09 *
|
0.09 *
|
|
Asalariado priv.
|
0.07 *
|
0.07 *
|
0.07 *
|
0.07 *
|
0.07
|
0.07 *
|
0.07 *
|
|
Cuenta propia
|
0.07 *
|
0.07 *
|
0.07 *
|
0.07 *
|
0.06 *
|
0.07 *
|
0.07 *
|
|
Desocupado
|
0.21 ***
|
0.21 ***
|
0.18 ***
|
0.18 ***
|
0.18 ***
|
0.18 ***
|
0.18 ***
|
|
Varón
|
0.01
|
0.01
|
0.01
|
0.01
|
0.01
|
0.01
|
0.01
|
|
Edad
|
-0.01 ***
|
-0.01 ***
|
-0.01 ***
|
-0.01 ***
|
-0.01 ***
|
-0.01 ***
|
-0.01 ***
|
|
Años educ.
|
0.03 ***
|
0.03 ***
|
0.03 ***
|
0.03 ***
|
0.03 ***
|
0.03 ***
|
0.03 ***
|
|
Desempleo
|
|
-0.09 ***
|
-0.09 ***
|
-0.09 ***
|
-0.09 ***
|
-0.08 ***
|
-0.09 ***
|
|
Informalidad
|
|
-0.03 ***
|
-0.03 ***
|
-0.03 ***
|
-0.03 ***
|
-0.03 ***
|
-0.03 ***
|
|
Empleo pub.
|
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
-0.01
|
-0.00
|
|
Brecha remun.
|
|
-0.02
|
-0.02
|
-0.02
|
-0.02
|
-0.02
|
-0.02
|
|
Desocupado*desempleo
|
|
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
0.07 ***
|
|
Random Effects
|
|
σ2
|
5.77
|
5.77
|
5.77
|
5.77
|
5.77
|
5.77
|
5.77
|
|
τ00
|
0.14 pais_anio
|
0.06 pais_anio
|
0.06 pais_anio
|
0.06 pais_anio
|
0.06 pais_anio
|
0.06 pais_anio
|
0.06 pais_anio
|
|
τ11
|
|
|
|
0.03 pais_anio.asal_pub_cwc
|
0.02 pais_anio.asal_pri_cwc
|
0.00 pais_anio.cuenta_prop_cwc
|
0.02 pais_anio.desocupado_cwc
|
|
ρ01
|
|
|
|
0.08 pais_anio
|
0.34 pais_anio
|
0.23 pais_anio
|
-0.14 pais_anio
|
|
N
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
42 pais_anio
|
|
Observations
|
53899
|
53899
|
53899
|
53899
|
53899
|
53899
|
53899
|
|
Marginal R2 / Conditional R2
|
0.013 / 0.038
|
0.027 / 0.037
|
0.027 / 0.038
|
0.028 / 0.038
|
0.025 / 0.037
|
0.026 / 0.037
|
0.027 / 0.038
|
|
AIC
|
247674.533
|
247679.687
|
247668.791
|
247668.413
|
247659.375
|
247671.954
|
247670.954
|
- p<0.05 ** p<0.01 *** p<0.001
|
## Data: base_ml
## Models:
## ideologia_null: ideologia ~ 1 + (1 | pais_anio)
## ideologia_ind: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_null 3 248352 248379 -124173 248346
## ideologia_ind 11 247619 247717 -123798 247597 749.28 8 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## ideologia_ind: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + (1 | pais_anio)
## ideologia_ind_grup: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind 11 247619 247717 -123798 247597
## ideologia_ind_grup 15 247593 247727 -123782 247563 33.231 4 1.071e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## ideologia_ind_grup: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + (1 | pais_anio)
## ideologia_ind_grup_int: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind_grup 15 247593 247727 -123782 247563
## ideologia_ind_grup_int 16 247576 247718 -123772 247544 19.288 1 1.124e-05
##
## ideologia_ind_grup
## ideologia_ind_grup_int ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## ideologia_ind_grup_int: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## ideologia_random_apub: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pub_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind_grup_int 16 247576 247718 -123772 247544
## ideologia_random_apub 18 247576 247736 -123770 247540 3.9398 2 0.1395
## Data: base_ml
## Models:
## ideologia_ind_grup_int: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## ideologia_random_apri: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + asal_pri_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind_grup_int 16 247576 247718 -123772 247544
## ideologia_random_apri 18 247567 247727 -123766 247531 12.934 2 0.001554
##
## ideologia_ind_grup_int
## ideologia_random_apri **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Data: base_ml
## Models:
## ideologia_ind_grup_int: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## ideologia_random_cuent: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + cuenta_prop_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind_grup_int 16 247576 247718 -123772 247544
## ideologia_random_cuent 18 247579 247740 -123772 247543 0.6837 2 0.7105
## Data: base_ml
## Models:
## ideologia_ind_grup_int: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 | pais_anio)
## ideologia_random_desoc: ideologia ~ 1 + patron_cwc + asal_pub_cwc + asal_pri_cwc + cuenta_prop_cwc + desocupado_cwc + sexo_cwc + edad_cwc + educ_cwc + desempleo_cgm + informalidad_cgm + empleo_pub_cgm + brecha_remun_cgm + desocupado_cwc * desempleo_cgm + (1 + desocupado_cwc | pais_anio)
## npar AIC BIC logLik deviance Chisq Df Pr(>Chisq)
## ideologia_ind_grup_int 16 247576 247718 -123772 247544
## ideologia_random_desoc 18 247579 247739 -123771 247543 1.2692 2 0.5301
Modelos de efectos fijos (2018)
Utilizando todas las variables laborales
Regresión lineal múltiple con control por países. 2018.
|
|
Democracia
|
Desigualdad
|
Desempleados
|
Ayuda pobres
|
Impuestos ricos
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
Patrón
|
-0.21
|
-0.11
|
0.14
|
0.05
|
0.01
|
|
Asalariado pub.
|
-0.31
|
0.08
|
0.30
|
0.19
|
0.13
|
|
Asalariado priv.
|
-0.26
|
0.04
|
0.31
|
0.10
|
-0.03
|
|
Cuenta propia
|
-0.18
|
-0.07
|
0.41
|
0.10
|
-0.10
|
|
Desocupado
|
-0.11
|
0.10
|
0.27 ***
|
0.08
|
0.05
|
|
Formal
|
-0.17
|
-0.12
|
0.90
|
0.56
|
-1.25
|
|
Informal
|
-0.30
|
0.02
|
0.95
|
0.66
|
-1.26
|
|
Directivos-profesionales
|
0.49
|
0.04
|
-1.02
|
-0.92
|
0.98
|
|
Téc-adm-vend
|
0.45
|
0.12
|
-1.25
|
-0.94
|
1.31
|
|
Trab. Man. calif
|
0.39
|
0.06
|
-1.48
|
-0.81
|
1.38
|
|
Trab. Man. No calif
|
0.50
|
0.14
|
-1.40
|
-0.73
|
1.42
|
|
Ideología (der-izq)
|
-0.02 *
|
0.01
|
0.06 ***
|
0.04 ***
|
0.02 **
|
|
Urbano
|
0.04
|
-0.02
|
-0.14 **
|
0.02
|
0.03
|
|
Varón
|
0.17 ***
|
-0.00
|
0.04
|
-0.02
|
0.03
|
|
Edad
|
0.02 ***
|
0.00
|
0.01 ***
|
-0.01 ***
|
0.01 ***
|
|
Años educ.
|
0.08 ***
|
0.04 ***
|
0.05 ***
|
-0.09 ***
|
-0.01 *
|
|
Observations
|
9933
|
10142
|
10185
|
10199
|
9999
|
|
R2 / R2 adjusted
|
0.053 / 0.051
|
0.007 / 0.005
|
0.027 / 0.025
|
0.050 / 0.048
|
0.007 / 0.005
|
|
AIC
|
37639.896
|
39702.361
|
42463.138
|
39302.554
|
40858.301
|
- p<0.05 ** p<0.01 *** p<0.001
|
Regresión logística binaria con control por países. 2018.
|
|
Corrupción
|
Golpe militar
|
Cierre congreso
|
Cierre corte
|
Simpatiza partido
|
|
Predictors
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
|
Intercepto
|
1.09
|
0.59 *
|
2.11 **
|
1.07
|
0.05 ***
|
|
Patrón
|
1.43
|
0.42
|
1.02
|
1.08
|
0.84
|
|
Asalariado pub.
|
1.38
|
0.49
|
1.08
|
1.13
|
0.79
|
|
Asalariado priv.
|
1.25
|
0.51
|
1.33
|
1.38
|
0.88
|
|
Cuenta propia
|
1.15
|
0.54
|
1.20
|
1.36
|
0.97
|
|
Desocupado
|
1.20
|
1.13
|
1.16
|
0.96
|
0.87
|
|
Formal
|
0.00
|
0.00
|
0.81
|
125360.79
|
0.83
|
|
Informal
|
0.00
|
0.00
|
0.86
|
123571.73
|
0.82
|
|
Directivos-profesionales
|
372165.23
|
261142.42
|
1.53
|
0.00
|
1.82
|
|
Téc-adm-vend
|
203297.33
|
164756.97
|
1.03
|
0.00
|
1.57
|
|
Trab. Man. calif
|
185183.37
|
143270.41
|
0.96
|
0.00
|
1.22
|
|
Trab. Man. No calif
|
198080.17
|
134378.22
|
1.10
|
0.00
|
1.24
|
|
Ideología (der-izq)
|
1.01
|
1.03 **
|
1.03 *
|
1.06 ***
|
0.99
|
|
Urbano
|
1.01
|
1.04
|
1.35 **
|
1.12
|
1.15
|
|
Varón
|
0.82 **
|
1.17 *
|
0.98
|
0.97
|
1.31 ***
|
|
Edad
|
0.99 ***
|
1.01 ***
|
1.00
|
1.00
|
1.02 ***
|
|
Años educ.
|
0.90 ***
|
1.06 ***
|
1.04 ***
|
1.11 ***
|
1.05 ***
|
|
Observations
|
4953
|
4910
|
5489
|
5345
|
10199
|
|
R2 Tjur
|
0.045
|
0.075
|
0.115
|
0.101
|
0.111
|
|
AIC
|
5647.697
|
5996.243
|
5632.445
|
5897.945
|
10012.764
|
- p<0.05 ** p<0.01 *** p<0.001
|
En el caso de las regresiones logísticas la categoría 1 de la
variable dependiente siempre es la opción más progre.
## GVIF Df GVIF^(1/(2*Df))
## categoria_ocup_f 53.905604 5 1.489922
## formal_estado2 563.625291 2 4.872453
## estatus_ocup_f 524.455971 4 2.187578
## ideologia_imp 1.032149 1 1.015947
## urbano 1.065313 1 1.032140
## sexo 1.102539 1 1.050018
## q2 1.203396 1 1.096994
## ed 1.449127 1 1.203797
## country_f 1.265574 6 1.019821
## GVIF Df GVIF^(1/(2*Df))
## categoria_ocup_f 53.263691 5 1.488138
## formal_estado2 575.482751 2 4.897879
## estatus_ocup_f 533.590804 4 2.192305
## ideologia_imp 1.030820 1 1.015293
## urbano 1.065696 1 1.032325
## sexo 1.104238 1 1.050827
## q2 1.205522 1 1.097963
## ed 1.449633 1 1.204007
## country_f 1.263722 6 1.019697
## GVIF Df GVIF^(1/(2*Df))
## categoria_ocup_f 5.814723e+01 5 1.501250
## formal_estado2 2.044182e+07 2 67.240338
## estatus_ocup_f 1.802812e+07 4 8.072235
## ideologia_imp 1.038370e+00 1 1.019005
## urbano 1.078046e+00 1 1.038290
## sexo 1.113300e+00 1 1.055130
## q2 1.270383e+00 1 1.127113
## ed 1.534095e+00 1 1.238586
## country_f 1.281856e+00 6 1.020908
## GVIF Df GVIF^(1/(2*Df))
## categoria_ocup_f 6.766083e+01 5 1.524171
## formal_estado2 1.533738e+07 2 62.580322
## estatus_ocup_f 1.327233e+07 4 7.769059
## ideologia_imp 1.030519e+00 1 1.015145
## urbano 1.056886e+00 1 1.028050
## sexo 1.106876e+00 1 1.052082
## q2 1.223316e+00 1 1.106036
## ed 1.485454e+00 1 1.218792
## country_f 1.296159e+00 6 1.021852
## GVIF Df GVIF^(1/(2*Df))
## categoria_ocup_f 43.793086 5 1.459286
## formal_estado2 334.323760 2 4.276041
## estatus_ocup_f 314.348076 4 2.051995
## ideologia_imp 1.030395 1 1.015084
## urbano 1.064708 1 1.031847
## sexo 1.115051 1 1.055960
## q2 1.223646 1 1.106185
## ed 1.427755 1 1.194887
## country_f 1.270103 6 1.020125
Para el caso de las regresiones logísticas no es recomendable
utilizar las tres variables laborales ya que están altamente
correlacionadas.
Utilizando solo categoría laboral
Regresión lineal múltiple con control por países. 2018.
|
|
Democracia
|
Desigualdad
|
Desempleados
|
Ayuda pobres
|
Impuestos ricos
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
Patrón
|
0.01
|
-0.11
|
-0.27 *
|
-0.15
|
0.08
|
|
Asalariado pub.
|
0.05
|
0.07
|
-0.07
|
-0.08
|
0.15 *
|
|
Asalariado priv.
|
0.00
|
0.04
|
-0.16 **
|
-0.16 **
|
0.08
|
|
Cuenta propia
|
-0.00
|
0.01
|
-0.08
|
-0.07
|
0.01
|
|
Desocupado
|
-0.10
|
0.11
|
0.25 ***
|
0.07
|
0.05
|
|
Ideología (der-izq)
|
-0.02 **
|
0.01
|
0.07 ***
|
0.04 ***
|
0.02 **
|
|
Urbano
|
0.04
|
-0.01
|
-0.13 *
|
0.04
|
0.05
|
|
Varón
|
0.16 ***
|
-0.01
|
0.02
|
-0.01
|
0.05
|
|
Edad
|
0.02 ***
|
0.00
|
0.01 ***
|
-0.01 ***
|
0.00 ***
|
|
Años educ.
|
0.08 ***
|
0.03 ***
|
0.06 ***
|
-0.09 ***
|
-0.02 ***
|
|
Observations
|
10461
|
10675
|
10718
|
10731
|
10530
|
|
R2 / R2 adjusted
|
0.053 / 0.052
|
0.007 / 0.005
|
0.024 / 0.023
|
0.051 / 0.049
|
0.006 / 0.004
|
|
AIC
|
39551.755
|
41737.799
|
44659.392
|
41362.528
|
42986.294
|
- p<0.05 ** p<0.01 *** p<0.001
|
Regresión logística binaria con control por países. 2018.
|
|
Corrupción
|
Golpe militar
|
Cierre congreso
|
Cierre corte
|
Simpatiza partido
|
|
Predictors
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
|
Intercepto
|
0.89
|
0.55 **
|
2.19 **
|
0.97
|
0.05 ***
|
|
Patrón
|
1.05
|
0.94
|
0.96
|
0.89
|
0.86
|
|
Asalariado pub.
|
1.20
|
1.21
|
1.14
|
0.83
|
1.03
|
|
Asalariado priv.
|
0.93
|
1.06
|
1.16
|
1.06
|
0.97
|
|
Cuenta propia
|
0.88
|
0.97
|
1.06
|
1.00
|
1.00
|
|
Desocupado
|
1.16
|
1.16
|
1.15
|
0.95
|
0.87
|
|
Ideología (der-izq)
|
1.00
|
1.04 **
|
1.03 *
|
1.06 ***
|
0.99
|
|
Urbano
|
1.02
|
1.01
|
1.33 **
|
1.08
|
1.14
|
|
Varón
|
0.85 *
|
1.20 **
|
0.97
|
0.93
|
1.29 ***
|
|
Edad
|
0.99 **
|
1.02 ***
|
1.00
|
1.00
|
1.02 ***
|
|
Años educ.
|
0.91 ***
|
1.07 ***
|
1.05 ***
|
1.13 ***
|
1.06 ***
|
|
Observations
|
5226
|
5161
|
5774
|
5639
|
10732
|
|
R2 Tjur
|
0.041
|
0.074
|
0.118
|
0.101
|
0.109
|
|
AIC
|
5935.825
|
6280.913
|
5851.909
|
6185.761
|
10546.156
|
- p<0.05 ** p<0.01 *** p<0.001
|
##
## F test for individual effects
##
## data: democracia7 ~ categoria_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 77.714, df1 = 6, df2 = 10444, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: reduc_desigualdad ~ categoria_ocup_f + ideologia_imp + urbano + ...
## F = 26.991, df1 = 6, df2 = 10658, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: desempleados ~ categoria_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 63.818, df1 = 6, df2 = 10701, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: ayuda_pobres ~ categoria_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 101.56, df1 = 6, df2 = 10714, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: impuestos_ricos ~ categoria_ocup_f + ideologia_imp + urbano + ...
## F = 58.349, df1 = 6, df2 = 10513, p-value < 2.2e-16
## alternative hypothesis: significant effects


Utilizando estatus ocupacional
Regresión lineal múltiple con control por países. 2018.
|
|
Democracia
|
Desigualdad
|
Desempleados
|
Ayuda pobres
|
Impuestos ricos
|
|
Predictors
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
Estimates
|
|
Directivos-profesionales
|
0.07
|
-0.06
|
0.15
|
-0.23 **
|
-0.25 **
|
|
Téc-adm-vend
|
0.01
|
0.02
|
-0.07
|
-0.25 ***
|
0.03
|
|
Trab. Man. calif
|
-0.04
|
-0.02
|
-0.28 ***
|
-0.11 **
|
0.07
|
|
Trab. Man. No calif
|
0.06
|
0.06
|
-0.19 **
|
-0.02
|
0.11
|
|
Ideología (der-izq)
|
-0.02 **
|
0.01
|
0.06 ***
|
0.04 ***
|
0.02 *
|
|
Urbano
|
0.03
|
-0.02
|
-0.15 **
|
0.03
|
0.03
|
|
Varón
|
0.16 ***
|
-0.00
|
0.06
|
-0.02
|
0.03
|
|
Edad
|
0.02 ***
|
0.00
|
0.01 ***
|
-0.01 ***
|
0.01 ***
|
|
Años educ.
|
0.08 ***
|
0.04 ***
|
0.05 ***
|
-0.09 ***
|
-0.01 *
|
|
Observations
|
10030
|
10239
|
10283
|
10297
|
10096
|
|
R2 / R2 adjusted
|
0.053 / 0.051
|
0.006 / 0.005
|
0.025 / 0.023
|
0.049 / 0.048
|
0.006 / 0.005
|
|
AIC
|
37980.868
|
40071.857
|
42882.916
|
39653.210
|
41257.830
|
- p<0.05 ** p<0.01 *** p<0.001
|
Regresión logística binaria con control por países. 2018.
|
|
Corrupción
|
Golpe militar
|
Cierre congreso
|
Cierre corte
|
Simpatiza partido
|
|
Predictors
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
Odds Ratios
|
|
Intercepto
|
1.18
|
0.62 *
|
2.23 **
|
1.05
|
0.05 ***
|
|
Directivos-profesionales
|
1.77 ***
|
1.76 **
|
1.43
|
1.53 *
|
1.35 *
|
|
Téc-adm-vend
|
0.94
|
1.13
|
0.99
|
1.10
|
1.18
|
|
Trab. Man. calif
|
0.85
|
0.96
|
0.96
|
0.93
|
0.95
|
|
Trab. Man. No calif
|
0.91
|
0.91
|
1.09
|
0.93
|
0.96
|
|
Ideología (der-izq)
|
1.01
|
1.03 **
|
1.03 *
|
1.06 ***
|
0.99
|
|
Urbano
|
1.01
|
1.03
|
1.32 **
|
1.11
|
1.13
|
|
Varón
|
0.82 **
|
1.19 **
|
0.99
|
0.98
|
1.30 ***
|
|
Edad
|
0.99 ***
|
1.01 ***
|
1.00
|
1.00
|
1.02 ***
|
|
Años educ.
|
0.90 ***
|
1.06 ***
|
1.05 ***
|
1.12 ***
|
1.05 ***
|
|
Observations
|
5005
|
4952
|
5549
|
5394
|
10298
|
|
R2 Tjur
|
0.044
|
0.074
|
0.117
|
0.100
|
0.110
|
|
AIC
|
5703.785
|
6045.964
|
5675.383
|
5954.904
|
10079.189
|
- p<0.05 ** p<0.01 *** p<0.001
|
##
## F test for individual effects
##
## data: democracia7 ~ estatus_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 70.8, df1 = 6, df2 = 10014, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: reduc_desigualdad ~ estatus_ocup_f + ideologia_imp + urbano + ...
## F = 26.371, df1 = 6, df2 = 10223, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: desempleados ~ estatus_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 57.892, df1 = 6, df2 = 10267, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: ayuda_pobres ~ estatus_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 94.338, df1 = 6, df2 = 10281, p-value < 2.2e-16
## alternative hypothesis: significant effects
##
## F test for individual effects
##
## data: impuestos_ricos ~ estatus_ocup_f + ideologia_imp + urbano + sexo + ...
## F = 52.62, df1 = 6, df2 = 10080, p-value < 2.2e-16
## alternative hypothesis: significant effects
Para todos los modelos es significativo utilizar efectos
fijos.

